Doğrulama raporu¶
Bu rapor her özniteliğin ürettiği sayıyı, dayandığı kaynağın yayımladığı sayıyla karşılaştırır. Amaç basit: bir sayıyı çalışmanızda kullanmadan önce onun literatürdeki değeri tuttuğunu görebilmeniz.
Durumlar ne anlama geliyor¶
| Anlamı | |
|---|---|
| ✅ birebir | Kaynağın yayımladığı sayıyla tolerans içinde aynı. Küçük bir farkın nedeni biliniyorsa satırın altında not olarak yazılır. |
| 🟡 belgelenmiş sapma | Fark toleransın dışında ve nedeni yazılı. Kaynağın ara değerleri yuvarlaması, ya da kaynağın sayılarının elle üretilmiş olması gibi. Sapmanın sonuca etkisi satırda anlatılır. |
| 🔍 açık | Kaynak formülü veriyor ama uygulanmış bir örnek vermiyor. Doğrulanabilir, henüz doğrulanmadı; formül ve sınır durumları kendi test dosyalarında sınanıyor. |
| ❌ uyuşmazlık | Açıklanmamış fark. Yayın kapısı: bir tane bile varsa sürüm çıkmaz. |
Aşağıdaki üç durum doğrulama adayı değildir — aranacak bir sayı yoktur:
| Anlamı | |
|---|---|
| ⚪ kaynak yok | Adlandırılmış bir literatür ölçüsü değil; saf tanım (punct_dash_ratio, uppercase_ratio). |
| ⚫ etiket şeması | Bir ölçü değil, dış bir şemanın kategorisini sayıyor (pos_noun_ratio → UD; zeyrek_case_loc_ratio → Zeyrek). Şema kategori tanımlar, ölçüm yayımlamaz. |
| 🔧 türev | Formül bir kaynaktan, uygulaması bu kütüphaneden. sent_len_entropy Shannon'ın entropisidir ama tümce uzunluklarına uygulanması bizim; long_sent_ratio'nun eşiği kendi kalibrasyonumuzdan gelir. Kimse bu ölçüyü yayımlamadı, dolayısıyla karşılaştırılacak sayı da yok. Kendi kalibrasyonumuza karşı sınamak kendi cevabımıza bakmak olurdu. |
Tolerans yayımlanan değerin %1'i (göreli). Kaynaklar ara değerleri yuvarlayarak bastığı için mutlak eşitlik beklenmiyor; göreli tolerans her ölçekte aynı anlama gelir.
Toleransı aşan fark otomatik olarak ❌ değildir. Belirleyici olan farkın büyüklüğü değil, nedeninin bilinip bilinmediğidir: nedeni ölçülmüş ve yazılmışsa satır 🟡, yazılmamışsa ❌ olur. Gerekçe bir mazeret değil, farkın nereden geldiğinin kanıtıdır — ilgili satırın altında okuyabilirsiniz.
Kanıtın iki türü¶
Uçtan uca satırlar kaynağın metnini boru hattından geçirir — yani tokenizasyon, heceleme ve tümce bölme de sınanır. Bunlar en güçlü kanıt.
Formül satırları fonksiyona girdileri doğrudan verir (örneğin "hece/sözcük 2,2 ve sözcük/tümce 4"). Formülü ve katsayıları doğrular, boru hattını doğrulamaz. Kaynak bir metin yayımlamamışsa elde olan budur.
Bu rapor testlerden üretilir — tests/test_kaynak_esligi.py ile aynı
karşılaştırma tablosunu okur, yani ikisi ayrışamaz. Diğer bilinen-değer
testleri kendi dosyalarında duruyor.
Türkçe — 208 anahtar, 233 satır¶
Bir anahtarın birden çok kaynak örneği olabilir; her biri ayrı satır.
Doğrulama adayı — 151 satır
| Durum | Satır sayısı |
|---|---|
| ✅ birebir | 46 |
| 🟡 belgelenmiş sapma | 2 |
| 🔍 açık — kaynakta sayısal örnek yok | 103 |
Doğrulama adayı olmayan — 82 satır. Bunlarda aranacak yayımlanmış bir sayı yoktur.
| Durum | Satır sayısı |
|---|---|
| ⚪ kaynak yok — saf tanım | 11 |
| ⚫ etiket şeması — ölçü değil | 67 |
| 🔧 türev — uygulaması bu kütüphaneye ait | 4 |
Sayısal karşılaştırması olanlar¶
| Anahtar | Kaynak | Örnek | Kanıt | Beklenen | Bizim | Fark | Durum |
|---|---|---|---|---|---|---|---|
entropy |
QUITA §6.1.12 | Text 1 · eq. (6.26); kaynak bit ile 6,438043 → × ln 2 | formül | 4.463 | 4.463 | +0.000 | ✅ |
entropy |
QUITA §6.1.12 | Text 2 · eq. (6.26); kaynak bit ile 6,395099 → × ln 2 | formül | 4.433 | 4.433 | +0.000 | ✅ |
ttr |
QUITA §6.1.1 | Text 1 · V/N = 119/179 | formül | 0.665 | 0.665 | -0.000 | ✅ |
ttr |
QUITA §6.1.1 | Text 2 · V/N = 121/202 = 0.599; kaynak 0.590 basmış (baskı hatası) | formül | 0.590 | 0.599 | +0.009 | 🟡 |
hapax_token_ratio |
QUITA §6.1.6 | Text 1 · 98/179 | formül | 0.547 | 0.547 | +0.000 | ✅ |
hapax_token_ratio |
QUITA §6.1.6 | Text 2 · 92/202 | formül | 0.455 | 0.455 | +0.000 | ✅ |
mtld |
McCarthy & Jarvis (2010) p.385 | kısmi faktör · TTR .887 → 40.4% | formül | 0.404 | 0.404 | +0.000 | ✅ |
h_point |
QUITA §6.1.2 | Text 1 · sıra 5 = sıklık 5 | formül | 5.000 | 5.000 | +0.000 | ✅ |
h_point |
QUITA §6.1.2 | Text 2 · ara değerleme, eq. (6.2) | formül | 4.750 | 4.750 | +0.000 | ✅ |
vocab_richness_r1 |
QUITA §6.1.3 | Text 1 · N=179, h=5 | formül | 0.835 | 0.835 | -0.000 | ✅ |
vocab_richness_r1 |
QUITA §6.1.3 | Text 2 · N=202, h=4.75 → ⌊h⌋=4 | formül | 0.838 | 0.838 | +0.000 | ✅ |
vocab_richness_r4 |
QUITA §6.1.9 | Text 1 · 1−G | formül | 0.696 | 0.696 | +0.000 | ✅ |
vocab_richness_r4 |
QUITA §6.1.9 | Text 2 · 1−G | formül | 0.649 | 0.649 | -0.000 | ✅ |
repeat_rate |
QUITA §6.1.4 | Text 1 · N=179 | formül | 0.020 | 0.020 | -0.000 | ✅ |
repeat_rate |
QUITA §6.1.4 | Text 2 · N=202 | formül | 0.021 | 0.021 | -0.000 | ✅ |
rr_mcintosh |
QUITA §6.1.5 | Text 1 · V=119 | formül | 0.946 | 0.946 | +0.000 | ✅ |
rr_mcintosh |
QUITA §6.1.5 | Text 2 · V=121 | formül | 0.939 | 0.939 | -0.000 | ✅ |
gini_coef |
QUITA §6.1.8 | Text 1 · m₁=41.88268156 | formül | 0.304 | 0.304 | -0.000 | ✅ |
gini_coef |
QUITA §6.1.8 | Text 2 · m₁=39.75742574 | formül | 0.351 | 0.351 | +0.000 | ✅ |
curve_length |
QUITA §6.1.10 | Text 1 · eq. (6.21) | formül | 129.356 | 129.356 | +0.000 | ✅ |
curve_length |
QUITA §6.1.10 | Text 2 · eq. (6.21) | formül | 134.279 | 134.279 | +0.000 | ✅ |
curve_length_r |
QUITA §6.1.11 | Text 1 · Lh=14.29145 | formül | 0.889 | 0.890 | +0.000 | ✅ |
curve_length_r |
QUITA §6.1.11 | Text 2 · Lh=18.03607 | formül | 0.866 | 0.866 | -0.000 | ✅ |
lambda_pa |
QUITA §6.1.7 | Text 1 · L·ln N/N, L=129.3559482; kaynak log₁₀ ile 1,628 → × ln 10 | formül | 3.749 | 3.749 | +0.000 | ✅ |
lambda_pa |
QUITA §6.1.7 | Text 2 · L·ln N/N, L=134.2787065; kaynak log₁₀ ile 1,5325 → × ln 10 | formül | 3.529 | 3.529 | -0.000 | ✅ |
adjusted_modulus |
QUITA §6.1.13 | Text 1 · M=24.01416249; kaynak log₁₀ ile 10,6594 → / ln 10 | formül | 4.629 | 4.629 | -0.000 | ✅ |
adjusted_modulus |
QUITA §6.1.13 | Text 2 · M=25.81931678; kaynak log₁₀ ile 11,19973 → / ln 10 | formül | 4.864 | 4.864 | +0.000 | ✅ |
writers_view_alpha |
QUITA §6.2.3 | Text 1 · arccos(−0.374487816) | formül | 1.955 | 1.955 | -0.000 | ✅ |
writers_view_alpha |
QUITA §6.2.3 | Text 2 · arccos(−0.269972586) | formül | 1.844 | 1.844 | +0.000 | ✅ |
activity_ratio |
QUITA §6.2.2 | Text 1 · 26 fiil / 14 sıfat | formül | 0.650 | 0.650 | +0.000 | ✅ |
activity_ratio |
QUITA §6.2.2 | Text 2 · 35 fiil / 8 sıfat | formül | 0.814 | 0.814 | -0.000 | ✅ |
arc_len_mean |
Jing & Liu (2015) p.164 | Figure 3 · 'Mr. Nixon was to…' | formül | 1.167 | 1.167 | +0.000 | ✅ |
arc_len_mean |
Liu (2008) eq. (1) | 'I actually live in Beijing' · 5/4 | formül | 1.250 | 1.250 | +0.000 | ✅ |
parse_depth_mean |
Jing & Liu (2015) p.164 | Figure 3 · MHD = 12/6 | formül | 2.000 | 2.000 | +0.000 | ✅ |
ari |
Kincaid et al. (1975) p.8, Table 1 | Appendix A · 18 passages, mean | uçtan uca | 12.300 | 11.763 | -0.537 | 🟡 |
coleman_liau |
Coleman & Liau (1975) p.284 | iki denklemin bileşimi · 13 sözcük, 2 tümce | formül | 7.704 | 7.705 | +0.000 | ✅ |
coleman_liau |
Coleman & Liau (1975) p.284, Table 1 | cloze 40.4% → 12. sınıf | formül | 12.000 | 11.994 | -0.006 | ✅ |
atesman |
Ateşman (1997) | Kalyoncu & Memiş (2024) Table 9 · Text 2 | uçtan uca | 23.094 | 23.094 | -0.000 | ✅ |
atesman |
Ateşman (1997) p.74 | kalibrasyon: en kolay metin | formül | 100.000 | 100.000 | -0.000 | ✅ |
atesman |
Ateşman (1997) p.74 | kalibrasyon: en zor metin | formül | 0.000 | 0.000 | +0.000 | ✅ |
cetinkaya_uzun |
Çetinkaya (2010) | Kalyoncu & Memiş (2024) Table 9 · Text 2 | uçtan uca | 23.084 | 23.084 | -0.000 | ✅ |
bezirci_yilmaz |
Bezirci & Yılmaz (2010) | Kalyoncu & Memiş (2024) Table 9 · Text 2 | uçtan uca | 30.423 | 30.392 | -0.031 | ✅ |
bezirci_yilmaz |
Bezirci & Yılmaz (2010) Table 5 | E7 3.03 · OKS 7 | formül | 4.610 | 4.605 | -0.005 | ✅ |
bezirci_yilmaz |
Bezirci & Yılmaz (2010) Table 5 | E7 8.3 · OKS 10 | formül | 9.110 | 9.110 | +0.000 | ✅ |
bezirci_yilmaz |
Bezirci & Yılmaz (2010) Table 5 | E7 18.82 · OKS 14 | formül | 16.230 | 16.232 | +0.002 | ✅ |
bezirci_yilmaz |
Bezirci & Yılmaz (2010) Table 3 | en kolay metnin H değerleri | formül | 3.030 | 3.025 | -0.005 | ✅ |
bezirci_yilmaz |
Bezirci & Yılmaz (2010) Table 3 | en zor metnin H değerleri | formül | 18.820 | 18.815 | -0.005 | ✅ |
bezirci_yilmaz |
Bezirci & Yılmaz (2010) Table 3 | ortalama H değerleri | formül | 8.300 | 8.341 | +0.041 | ✅ |
ttr sapması: Kaynağın kendi sayıları (V=121, N=202) 121/202 = 0,599 verir; basılan 0,590 bu aritmetikle tutmuyor (baskı hatası). Bizim değer aritmetiğe uyuyor; fark yayımlanan değerin %1,5'i.
ari sapması: Kaynağın sayıları 1975'te daktiloya takılı mekanik bir sayaçla elle üretildi (Ek B, ARI talimatı). 18 pasajın 17'sinde, kaynağın ARI'sını verecek vuruş sayısı bizim saydığımızın 0,996-1,041 katı — yani birkaç karakterlik fark. Pasaj 2 aykırı (oran 1,145) ve kaynağın kendi iki sayısı orada çelişiyor: Tablo 1'in ARI 20,3'ü vuruş/sözcük 6,270 gerektiriyor, metnin gerçek değeri 5,475; üstelik o ARI'nın ima ettiği sözcük/tümce FKGL'yi 18,70 yapıyor, oysa Tablo 2 16,7 basmış. Bizim vuruş tanımımız ayrıca sınandı: boşluğu sayıma katmak farkı 0,54'ten 4,32'ye çıkarıyor, yani boşluksuz sayım doğru.
bezirci_yilmaz sapması: Makale H6 ara değerini yuvarlamış; fark 0,031 ve iki değer de aynı okunabilirlik sınıfına düşüyor (akademik, 16+).
bezirci_yilmaz sapması: Makale H6 ortalamasını 0,07 basmış, ama 8,30'u veren değer ~0,0684. 26,25 katsayısı bu yuvarlamayı 0,041'e büyütüyor; katsayıların kendisi doğru.
🔍 Açık — doğrulanabilir, henüz doğrulanmadı¶
103 anahtar. Kaynak formülü yayımlamış ama o formülün uygulandığı bir sayısal örnek vermemiş. Nicel dilbilimde bu olağandır: Yule (1944) K'yı tanımlar, bir romanda K'nın kaç çıktığını basmaz. Bu satırlar test edilmiyor demek değildir — formül ve sınır durumları kendi test dosyalarında sınanıyor; burada takip edilen yalnız kaynağın sayısıyla karşılaştırma.
| Anahtar | Kaynak | Durum |
|---|---|---|
word_count |
de Vel (2000) Table 2, attribute 1 "Total number of words"; Zheng et al. (2006) Table 3, p.385, no. 54 "Total number of words (M)" | 🔍 |
word_len_mean |
Mendenhall (1887) p.237 "mean word-length"; computed as letters per word, p.241 | 🔍 |
yule_k |
Yule (1944) p.53, eq. (3.22) | 🔍 |
simpson_d |
Simpson (1949), as cited in Bestgen (2023) | 🔍 |
type_count |
Tweedie & Baayen (1998) p.325, the vocabulary size V(N); Zheng et al. (2006) Table 3, p.385, no. 60 "Total different words/M", here not divided by M | 🔍 |
hapax_count |
Tweedie & Baayen (1998) p.325, V(1, N) "the number of hapax legomena"; Zheng et al. (2006) Table 3, p.385, no. 61 "Hapax legomena" ("Frequency of once-occurring words") | 🔍 |
dislegomena_count |
Tweedie & Baayen (1998) p.329, V(2, N) "dis legomena"; Zheng et al. (2006) Table 3, p.385, no. 62 "Hapax dislegomena" ("Frequency of twice-occurring words") | 🔍 |
brunet_w |
Brunet (1978), as cited in Tweedie & Baayen (1998) p.328, eq. (10) | 🔍 |
hapax_ratio |
de Vel (2000) Table 2, attribute 14 "Ratio of words used once to total number of vocabulary words" | 🔍 |
mattr |
Covington & McFall (2010); default window 50 — C&M recommend a window of 500; 50 is used here so that texts of 100+ words can be measured (mattr needs 2 × window) | 🔍 |
herdan_c |
Herdan (1960/1964), as cited in Tweedie & Baayen (1998) p.327, eq. (5) | 🔍 |
dugast_u |
Dugast (1978), as cited in Malvern et al. (2004) eq. 2.7 | 🔍 |
guiraud_r |
Guiraud (1954) p.53, alternative form (all word types), as cited in Daller (2010); his actual law is V/√(2N), content words only | 🔍 |
cttr |
Carroll (1964), as cited in Torruella & Capsada (2013) p.448 | 🔍 |
summer_s |
Somers (1966), as cited in Torruella & Capsada (2013) p.448, where it is named "Summer"; the source gives no logarithm base, the natural logarithm is this library's choice | 🔍 |
maas_a2 |
Maas (1972), as cited in Tweedie & Baayen (1998) p.327, eq. (7); natural logarithm, which reproduces the values in Torruella & Capsada (2013) Table 1; all logarithms in this library are natural | 🔍 |
herdan_vm |
Herdan (1955), as cited in Tweedie & Baayen (1998) p.330, eq. (18) | 🔍 |
honore_r |
Honoré (1979), as cited in Tweedie & Baayen (1998) p.329, eq. (11) | 🔍 |
heaps_beta |
Heaps (1978), as cited in Manning et al. (2008) §5.1.1 | 🔍 |
sichel_s |
Sichel (1975); formula from Malvern et al. (2004) eq. 3.10 | 🔍 |
noun_variation |
Lu (2012) Table 2 | 🔍 |
verb_variation |
Lu (2012) Table 2 | 🔍 |
adj_variation |
Lu (2012) Table 2 | 🔍 |
adv_variation |
Lu (2012) Table 2 | 🔍 |
zipf_exponent |
Piantadosi (2014) eq. (2); the same source criticises estimating r and f(r) from the same corpus | 🔍 |
zipf_r2 |
Piantadosi (2014) eq. (2); the same source criticises estimating r and f(r) from the same corpus | 🔍 |
zipf_mandelbrot_q |
Piantadosi (2014) eq. (2); the same source criticises estimating r and f(r) from the same corpus | 🔍 |
zipf_mandelbrot_s |
Piantadosi (2014) eq. (2); the same source criticises estimating r and f(r) from the same corpus | 🔍 |
wordfreq_mean |
van Heuven et al. (2014) (Zipf scale) | 🔍 |
wordfreq_rare_ratio |
van Heuven et al. (2014) Table 1 (Zipf ≤ 3 = low frequency) | 🔍 |
vocd_d |
Malvern et al. (2004) pp.56–57; procedure from McCarthy & Jarvis (2010) p.383 | 🔍 |
hdd |
McCarthy & Jarvis (2007), as cited in McCarthy & Jarvis (2010) p.383 | 🔍 |
msttr |
Johnson (1944), as cited in Malvern et al. (2004) p.25 and McCarthy & Jarvis (2010) p.385 | 🔍 |
thematic_concentration |
QUITA §6.2.5 | 🔍 |
secondary_thematic_concentration |
QUITA §6.2.6 | 🔍 |
sent_len_mean |
Flesch (1948) p.223, element (1) "Average Sentence Length in Words" | 🔍 |
sent_len_median |
Yule (1939) p.369, median sentence length alongside the mean | 🔍 |
sent_count |
de Vel (2000) Table 2, attribute 3 "Number of sentences"; Zheng et al. (2006) Table 3, p.385, no. 247 "Total number of sentences" | 🔍 |
sent_len_char_mean |
Zheng et al. (2006) Table 3, p.385, no. 58 "Average sentence length in terms of character" | 🔍 |
para_count |
Zheng et al. (2006) Table 3, p.385, no. 248 "Total number of paragraphs" | 🔍 |
para_len_mean |
Zheng et al. (2006) Table 3, p.385, no. 251 "Number of words per paragraph" | 🔍 |
sents_per_para_mean |
Zheng et al. (2006) Table 3, p.385, no. 249 "Number of sentences per paragraph" | 🔍 |
pronoun_ratio |
Deutsch, Jasbi & Shieber (2020) Table 6 "pronouns per word", listed among existing features; original source not traced | 🔍 |
verb_dist_mean |
QUITA §6.2.1 | 🔍 |
lexical_density |
Lu (2012); definition in the broad Hallidayan sense — all open-class words | 🔍 |
posddev |
Deutsch, Jasbi & Shieber (2020) Definition 3.3 (POSDdev); computed over ratios, 12 UD tags | 🔍 |
posdiv |
Deutsch, Jasbi & Shieber (2020) Definition 3.4 (POSdiv); natural logarithm (nats), the source uses bits | 🔍 |
zeyrek_suffix_bigram_entropy |
Shannon (1948) — the entropy formula; Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | 🔍 |
front_vowel_ratio |
Göksel & Kerslake (2005) ch. 2 (the vowel system, front/back) | 🔍 |
back_vowel_ratio |
Göksel & Kerslake (2005) ch. 2 (the vowel system, front/back) | 🔍 |
harmony_fronting_ratio |
Göksel & Kerslake (2005) §3.1 (fronting harmony); exceptions §3.4 — the measure counts them as disharmonic | 🔍 |
harmony_rounding_ratio |
Göksel & Kerslake (2005) §3.1 (rounding harmony); strictly a suffix phenomenon, measured here as a whole-word pattern | 🔍 |
syllable_count |
Kincaid et al. (1975) p.38, "Instructions for Recalculated Flesch Formula", step 3 "Count the number of syllables" | 🔍 |
syllable_mean |
Flesch (1948) Formula A, wl; unit there = syllables per 100 words, here per word | 🔍 |
syllable_1_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_2_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_3_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_4_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_5_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_6plus_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
lix |
Björnsson (1968), as cited in Anderson (1983) p.490; long word = 7+ letters | 🔍 |
long_word_ratio |
Anderson (1983); long word = 7+ letters | 🔍 |
char_count |
de Vel (2000) Table 2, attribute 8 "Number of characters"; Zheng et al. (2006) Table 3, p.385, no. 1 "Total number of characters (C)" | 🔍 |
digit_ratio |
de Vel et al. (2001) Table 2, p.60 "Total number of digit characters in words/C"; here digits anywhere in the text | 🔍 |
punct_count |
de Vel et al. (2001) Table 2, p.60 "Total number of punctuations/C", here not divided by C | 🔍 |
punct_comma_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_period_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_semicolon_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_exclamation_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_colon_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_quote_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_question_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_char_ratio |
de Vel et al. (2001) Table 2, p.60 "Total number of punctuations/C" | 🔍 |
whitespace_ratio |
de Vel et al. (2001) Table 2, p.60 "Total number of white-space characters/C" | 🔍 |
char_a_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_b_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_c_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_ç_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_d_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_e_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_f_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_g_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_ğ_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_h_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_ı_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_i_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_j_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_k_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_l_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_m_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_n_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_o_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_ö_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_p_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_r_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_s_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_ş_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_t_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_u_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_ü_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_v_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_y_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_z_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
Doğrulama adayı olmayanlar¶
82 anahtar. ⚪ olanlar saf tanım (punct_dash_ratio, uppercase_ratio) — adlandırılmış bir literatür ölçüsü değil. ⚫ olanlar bir ölçü değil, dış bir etiket şemasının kategorisini sayıyor; şema kategori tanımlar, ölçüm yayımlamaz. 🔧 olanların formülü bir kaynaktan gelir ama uygulaması bu kütüphaneye aittir. Üçünde de aranacak bir sayı yok.
| Anahtar | Kaynak | Durum |
|---|---|---|
lemma_count |
— | ⚪ |
short_sent_ratio |
This library's threshold calibration (docs/threshold-calibration.md); TR 4, EN 8 — 15th percentile of newspaper columns under the default sentence and word rules. Note: the TR value coincides with Ateşman (1997) p.74, where the easiest text has a mean sentence length of 4 words; that is a text mean, not a threshold, so it is not the source. Calibrated on newspaper columns only | 🔧 |
long_sent_ratio |
This library's threshold calibration (docs/threshold-calibration.md); TR 17, EN 32 — 85th percentile of newspaper columns under the default sentence and word rules. Ateşman's 30 was not used: that is the mean of the hardest text, not a single-sentence threshold (in Turkish newspaper columns 30 words is above the 95th percentile, so as a threshold it would almost never fire). Calibrated on newspaper columns only | 🔧 |
sent_len_entropy |
Shannon (1948) — the entropy formula; applying it to the distribution of sentence lengths is this library's own decision | 🔧 |
pos_noun_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_propn_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_verb_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_adj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_adv_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_det_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_adp_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_intj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_cconj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_sconj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_num_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_aux_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
question_sent_ratio |
— | ⚪ |
sentfinal_noun_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_propn_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_verb_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_adj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_adv_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_det_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_adp_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_intj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_cconj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_sconj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_num_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_aux_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_pron_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_other_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
surface_per_lemma |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
tense_past_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
tense_pres_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
tense_fut_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
aspect_perf_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
aspect_imp_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
aspect_prog_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_nom_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_acc_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_dat_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_loc_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_abl_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_gen_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
person_1_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
person_2_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
person_3_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
number_sing_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
number_plur_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
voice_pass_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
zeyrek_agglutination_depth |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_suffix_char_length_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_derivational_suffix_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_tense_past_def_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_tense_past_nar_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_tense_present_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_tense_future_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_modal_possibility_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_modal_necessity_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_negation_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_passive_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_plural_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_case_acc_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_case_dat_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_case_loc_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_case_abl_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_case_gen_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_case_ins_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_conditional_suffix_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_causative_suffix_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_question_particle_ratio |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
zeyrek_verb_suffix_diversity |
Zeyrek (a Python port of Zemberek's morphotactics); tag set from Akın & Akın (2007) | ⚫ |
vowel_ratio |
— | ⚪ |
sent_syllable_mean |
— | ⚪ |
punct_dash_ratio |
— | ⚪ |
punct_ellipsis_ratio |
— | ⚪ |
punct_paren_ratio |
— | ⚪ |
punct_entropy |
Shannon (1948) — the entropy formula; applying it to the distribution of punctuation types is this library's own decision | 🔧 |
consecutive_punct_ratio |
— | ⚪ |
punct_variety |
— | ⚪ |
uppercase_ratio |
— | ⚪ |
all_caps_word_ratio |
— | ⚪ |
İngilizce — 181 anahtar, 198 satır¶
Bir anahtarın birden çok kaynak örneği olabilir; her biri ayrı satır.
Doğrulama adayı — 137 satır
| Durum | Satır sayısı |
|---|---|
| ✅ birebir | 35 |
| 🟡 belgelenmiş sapma | 3 |
| 🔍 açık — kaynakta sayısal örnek yok | 99 |
Doğrulama adayı olmayan — 61 satır. Bunlarda aranacak yayımlanmış bir sayı yoktur.
| Durum | Satır sayısı |
|---|---|
| ⚪ kaynak yok — saf tanım | 11 |
| ⚫ etiket şeması — ölçü değil | 45 |
| 🔧 türev — uygulaması bu kütüphaneye ait | 5 |
Sayısal karşılaştırması olanlar¶
| Anahtar | Kaynak | Örnek | Kanıt | Beklenen | Bizim | Fark | Durum |
|---|---|---|---|---|---|---|---|
entropy |
QUITA §6.1.12 | Text 1 · eq. (6.26); kaynak bit ile 6,438043 → × ln 2 | formül | 4.463 | 4.463 | +0.000 | ✅ |
entropy |
QUITA §6.1.12 | Text 2 · eq. (6.26); kaynak bit ile 6,395099 → × ln 2 | formül | 4.433 | 4.433 | +0.000 | ✅ |
ttr |
QUITA §6.1.1 | Text 1 · V/N = 119/179 | formül | 0.665 | 0.665 | -0.000 | ✅ |
ttr |
QUITA §6.1.1 | Text 2 · V/N = 121/202 = 0.599; kaynak 0.590 basmış (baskı hatası) | formül | 0.590 | 0.599 | +0.009 | 🟡 |
hapax_token_ratio |
QUITA §6.1.6 | Text 1 · 98/179 | formül | 0.547 | 0.547 | +0.000 | ✅ |
hapax_token_ratio |
QUITA §6.1.6 | Text 2 · 92/202 | formül | 0.455 | 0.455 | +0.000 | ✅ |
mtld |
McCarthy & Jarvis (2010) p.385 | kısmi faktör · TTR .887 → 40.4% | formül | 0.404 | 0.404 | +0.000 | ✅ |
h_point |
QUITA §6.1.2 | Text 1 · sıra 5 = sıklık 5 | formül | 5.000 | 5.000 | +0.000 | ✅ |
h_point |
QUITA §6.1.2 | Text 2 · ara değerleme, eq. (6.2) | formül | 4.750 | 4.750 | +0.000 | ✅ |
vocab_richness_r1 |
QUITA §6.1.3 | Text 1 · N=179, h=5 | formül | 0.835 | 0.835 | -0.000 | ✅ |
vocab_richness_r1 |
QUITA §6.1.3 | Text 2 · N=202, h=4.75 → ⌊h⌋=4 | formül | 0.838 | 0.838 | +0.000 | ✅ |
vocab_richness_r4 |
QUITA §6.1.9 | Text 1 · 1−G | formül | 0.696 | 0.696 | +0.000 | ✅ |
vocab_richness_r4 |
QUITA §6.1.9 | Text 2 · 1−G | formül | 0.649 | 0.649 | -0.000 | ✅ |
repeat_rate |
QUITA §6.1.4 | Text 1 · N=179 | formül | 0.020 | 0.020 | -0.000 | ✅ |
repeat_rate |
QUITA §6.1.4 | Text 2 · N=202 | formül | 0.021 | 0.021 | -0.000 | ✅ |
rr_mcintosh |
QUITA §6.1.5 | Text 1 · V=119 | formül | 0.946 | 0.946 | +0.000 | ✅ |
rr_mcintosh |
QUITA §6.1.5 | Text 2 · V=121 | formül | 0.939 | 0.939 | -0.000 | ✅ |
gini_coef |
QUITA §6.1.8 | Text 1 · m₁=41.88268156 | formül | 0.304 | 0.304 | -0.000 | ✅ |
gini_coef |
QUITA §6.1.8 | Text 2 · m₁=39.75742574 | formül | 0.351 | 0.351 | +0.000 | ✅ |
curve_length |
QUITA §6.1.10 | Text 1 · eq. (6.21) | formül | 129.356 | 129.356 | +0.000 | ✅ |
curve_length |
QUITA §6.1.10 | Text 2 · eq. (6.21) | formül | 134.279 | 134.279 | +0.000 | ✅ |
curve_length_r |
QUITA §6.1.11 | Text 1 · Lh=14.29145 | formül | 0.889 | 0.890 | +0.000 | ✅ |
curve_length_r |
QUITA §6.1.11 | Text 2 · Lh=18.03607 | formül | 0.866 | 0.866 | -0.000 | ✅ |
lambda_pa |
QUITA §6.1.7 | Text 1 · L·ln N/N, L=129.3559482; kaynak log₁₀ ile 1,628 → × ln 10 | formül | 3.749 | 3.749 | +0.000 | ✅ |
lambda_pa |
QUITA §6.1.7 | Text 2 · L·ln N/N, L=134.2787065; kaynak log₁₀ ile 1,5325 → × ln 10 | formül | 3.529 | 3.529 | -0.000 | ✅ |
adjusted_modulus |
QUITA §6.1.13 | Text 1 · M=24.01416249; kaynak log₁₀ ile 10,6594 → / ln 10 | formül | 4.629 | 4.629 | -0.000 | ✅ |
adjusted_modulus |
QUITA §6.1.13 | Text 2 · M=25.81931678; kaynak log₁₀ ile 11,19973 → / ln 10 | formül | 4.864 | 4.864 | +0.000 | ✅ |
writers_view_alpha |
QUITA §6.2.3 | Text 1 · arccos(−0.374487816) | formül | 1.955 | 1.955 | -0.000 | ✅ |
writers_view_alpha |
QUITA §6.2.3 | Text 2 · arccos(−0.269972586) | formül | 1.844 | 1.844 | +0.000 | ✅ |
activity_ratio |
QUITA §6.2.2 | Text 1 · 26 fiil / 14 sıfat | formül | 0.650 | 0.650 | +0.000 | ✅ |
activity_ratio |
QUITA §6.2.2 | Text 2 · 35 fiil / 8 sıfat | formül | 0.814 | 0.814 | -0.000 | ✅ |
arc_len_mean |
Jing & Liu (2015) p.164 | Figure 3 · 'Mr. Nixon was to…' | formül | 1.167 | 1.167 | +0.000 | ✅ |
arc_len_mean |
Liu (2008) eq. (1) | 'I actually live in Beijing' · 5/4 | formül | 1.250 | 1.250 | +0.000 | ✅ |
parse_depth_mean |
Jing & Liu (2015) p.164 | Figure 3 · MHD = 12/6 | formül | 2.000 | 2.000 | +0.000 | ✅ |
ari |
Kincaid et al. (1975) p.8, Table 1 | Appendix A · 18 passages, mean | uçtan uca | 12.300 | 11.763 | -0.537 | 🟡 |
coleman_liau |
Coleman & Liau (1975) p.284 | iki denklemin bileşimi · 13 sözcük, 2 tümce | formül | 7.704 | 7.705 | +0.000 | ✅ |
coleman_liau |
Coleman & Liau (1975) p.284, Table 1 | cloze 40.4% → 12. sınıf | formül | 12.000 | 11.994 | -0.006 | ✅ |
flesch_kincaid_grade |
Kincaid et al. (1975) p.12, Table 2 | Appendix A · 18 passages, mean | uçtan uca | 10.700 | 10.326 | -0.374 | 🟡 |
ttr sapması: Kaynağın kendi sayıları (V=121, N=202) 121/202 = 0,599 verir; basılan 0,590 bu aritmetikle tutmuyor (baskı hatası). Bizim değer aritmetiğe uyuyor; fark yayımlanan değerin %1,5'i.
ari sapması: Kaynağın sayıları 1975'te daktiloya takılı mekanik bir sayaçla elle üretildi (Ek B, ARI talimatı). 18 pasajın 17'sinde, kaynağın ARI'sını verecek vuruş sayısı bizim saydığımızın 0,996-1,041 katı — yani birkaç karakterlik fark. Pasaj 2 aykırı (oran 1,145) ve kaynağın kendi iki sayısı orada çelişiyor: Tablo 1'in ARI 20,3'ü vuruş/sözcük 6,270 gerektiriyor, metnin gerçek değeri 5,475; üstelik o ARI'nın ima ettiği sözcük/tümce FKGL'yi 18,70 yapıyor, oysa Tablo 2 16,7 basmış. Bizim vuruş tanımımız ayrıca sınandı: boşluğu sayıma katmak farkı 0,54'ten 4,32'ye çıkarıyor, yani boşluksuz sayım doğru.
flesch_kincaid_grade sapması: Aynı elle sayım kaynağı. Pasaj başına sapma 18'in 15'inde 0,6'nın altında; pasaj 12 aykırı (-4,28) ve o pasaj FRE bandını da tutturmuyor, yani sapma tek bir pasajda yoğunlaşıyor. Ortalamalar arasındaki fark 0,37 sınıf düzeyi — okunabilirlik sınıflandırmasını değiştirmeyecek kadar küçük.
🔍 Açık — doğrulanabilir, henüz doğrulanmadı¶
99 anahtar. Kaynak formülü yayımlamış ama o formülün uygulandığı bir sayısal örnek vermemiş. Nicel dilbilimde bu olağandır: Yule (1944) K'yı tanımlar, bir romanda K'nın kaç çıktığını basmaz. Bu satırlar test edilmiyor demek değildir — formül ve sınır durumları kendi test dosyalarında sınanıyor; burada takip edilen yalnız kaynağın sayısıyla karşılaştırma.
| Anahtar | Kaynak | Durum |
|---|---|---|
word_count |
de Vel (2000) Table 2, attribute 1 "Total number of words"; Zheng et al. (2006) Table 3, p.385, no. 54 "Total number of words (M)" | 🔍 |
word_len_mean |
Mendenhall (1887) p.237 "mean word-length"; computed as letters per word, p.241 | 🔍 |
yule_k |
Yule (1944) p.53, eq. (3.22) | 🔍 |
simpson_d |
Simpson (1949), as cited in Bestgen (2023) | 🔍 |
type_count |
Tweedie & Baayen (1998) p.325, the vocabulary size V(N); Zheng et al. (2006) Table 3, p.385, no. 60 "Total different words/M", here not divided by M | 🔍 |
hapax_count |
Tweedie & Baayen (1998) p.325, V(1, N) "the number of hapax legomena"; Zheng et al. (2006) Table 3, p.385, no. 61 "Hapax legomena" ("Frequency of once-occurring words") | 🔍 |
dislegomena_count |
Tweedie & Baayen (1998) p.329, V(2, N) "dis legomena"; Zheng et al. (2006) Table 3, p.385, no. 62 "Hapax dislegomena" ("Frequency of twice-occurring words") | 🔍 |
brunet_w |
Brunet (1978), as cited in Tweedie & Baayen (1998) p.328, eq. (10) | 🔍 |
hapax_ratio |
de Vel (2000) Table 2, attribute 14 "Ratio of words used once to total number of vocabulary words" | 🔍 |
mattr |
Covington & McFall (2010); default window 50 — C&M recommend a window of 500; 50 is used here so that texts of 100+ words can be measured (mattr needs 2 × window) | 🔍 |
herdan_c |
Herdan (1960/1964), as cited in Tweedie & Baayen (1998) p.327, eq. (5) | 🔍 |
dugast_u |
Dugast (1978), as cited in Malvern et al. (2004) eq. 2.7 | 🔍 |
guiraud_r |
Guiraud (1954) p.53, alternative form (all word types), as cited in Daller (2010); his actual law is V/√(2N), content words only | 🔍 |
cttr |
Carroll (1964), as cited in Torruella & Capsada (2013) p.448 | 🔍 |
summer_s |
Somers (1966), as cited in Torruella & Capsada (2013) p.448, where it is named "Summer"; the source gives no logarithm base, the natural logarithm is this library's choice | 🔍 |
maas_a2 |
Maas (1972), as cited in Tweedie & Baayen (1998) p.327, eq. (7); natural logarithm, which reproduces the values in Torruella & Capsada (2013) Table 1; all logarithms in this library are natural | 🔍 |
herdan_vm |
Herdan (1955), as cited in Tweedie & Baayen (1998) p.330, eq. (18) | 🔍 |
honore_r |
Honoré (1979), as cited in Tweedie & Baayen (1998) p.329, eq. (11) | 🔍 |
heaps_beta |
Heaps (1978), as cited in Manning et al. (2008) §5.1.1 | 🔍 |
sichel_s |
Sichel (1975); formula from Malvern et al. (2004) eq. 3.10 | 🔍 |
noun_variation |
Lu (2012) Table 2 | 🔍 |
verb_variation |
Lu (2012) Table 2 | 🔍 |
adj_variation |
Lu (2012) Table 2 | 🔍 |
adv_variation |
Lu (2012) Table 2 | 🔍 |
zipf_exponent |
Piantadosi (2014) eq. (2); the same source criticises estimating r and f(r) from the same corpus | 🔍 |
zipf_r2 |
Piantadosi (2014) eq. (2); the same source criticises estimating r and f(r) from the same corpus | 🔍 |
zipf_mandelbrot_q |
Piantadosi (2014) eq. (2); the same source criticises estimating r and f(r) from the same corpus | 🔍 |
zipf_mandelbrot_s |
Piantadosi (2014) eq. (2); the same source criticises estimating r and f(r) from the same corpus | 🔍 |
wordfreq_mean |
van Heuven et al. (2014) (Zipf scale) | 🔍 |
wordfreq_rare_ratio |
van Heuven et al. (2014) Table 1 (Zipf ≤ 3 = low frequency) | 🔍 |
vocd_d |
Malvern et al. (2004) pp.56–57; procedure from McCarthy & Jarvis (2010) p.383 | 🔍 |
hdd |
McCarthy & Jarvis (2007), as cited in McCarthy & Jarvis (2010) p.383 | 🔍 |
msttr |
Johnson (1944), as cited in Malvern et al. (2004) p.25 and McCarthy & Jarvis (2010) p.385 | 🔍 |
thematic_concentration |
QUITA §6.2.5 | 🔍 |
secondary_thematic_concentration |
QUITA §6.2.6 | 🔍 |
sent_len_mean |
Flesch (1948) p.223, element (1) "Average Sentence Length in Words" | 🔍 |
sent_len_median |
Yule (1939) p.369, median sentence length alongside the mean | 🔍 |
sent_count |
de Vel (2000) Table 2, attribute 3 "Number of sentences"; Zheng et al. (2006) Table 3, p.385, no. 247 "Total number of sentences" | 🔍 |
sent_len_char_mean |
Zheng et al. (2006) Table 3, p.385, no. 58 "Average sentence length in terms of character" | 🔍 |
para_count |
Zheng et al. (2006) Table 3, p.385, no. 248 "Total number of paragraphs" | 🔍 |
para_len_mean |
Zheng et al. (2006) Table 3, p.385, no. 251 "Number of words per paragraph" | 🔍 |
sents_per_para_mean |
Zheng et al. (2006) Table 3, p.385, no. 249 "Number of sentences per paragraph" | 🔍 |
pronoun_ratio |
Deutsch, Jasbi & Shieber (2020) Table 6 "pronouns per word", listed among existing features; original source not traced | 🔍 |
verb_dist_mean |
QUITA §6.2.1 | 🔍 |
lexical_density |
Lu (2012); definition in the broad Hallidayan sense — all open-class words | 🔍 |
posddev |
Deutsch, Jasbi & Shieber (2020) Definition 3.3 (POSDdev); computed over ratios, 12 UD tags | 🔍 |
posdiv |
Deutsch, Jasbi & Shieber (2020) Definition 3.4 (POSdiv); natural logarithm (nats), the source uses bits | 🔍 |
front_vowel_ratio |
Göksel & Kerslake (2005) ch. 2 (the vowel system, front/back) | 🔍 |
back_vowel_ratio |
Göksel & Kerslake (2005) ch. 2 (the vowel system, front/back) | 🔍 |
syllable_count |
Kincaid et al. (1975) p.38, "Instructions for Recalculated Flesch Formula", step 3 "Count the number of syllables" | 🔍 |
syllable_mean |
Flesch (1948) Formula A, wl; unit there = syllables per 100 words, here per word | 🔍 |
syllable_1_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_2_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_3_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_4_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_5_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
syllable_6plus_ratio |
Bezirci & Yılmaz (2010) Table 1-c | 🔍 |
lix |
Björnsson (1968), as cited in Anderson (1983) p.490; long word = 7+ letters | 🔍 |
long_word_ratio |
Anderson (1983); long word = 7+ letters | 🔍 |
flesch_reading_ease |
Flesch (1948) Formula A; coefficient .846, unit = syllables per 100 words | 🔍 |
smog |
McLaughlin (1969) p.643, Table 1, eq. (d); p = polysyllabic words in a 30-sentence sample | 🔍 |
char_count |
de Vel (2000) Table 2, attribute 8 "Number of characters"; Zheng et al. (2006) Table 3, p.385, no. 1 "Total number of characters (C)" | 🔍 |
digit_ratio |
de Vel et al. (2001) Table 2, p.60 "Total number of digit characters in words/C"; here digits anywhere in the text | 🔍 |
punct_count |
de Vel et al. (2001) Table 2, p.60 "Total number of punctuations/C", here not divided by C | 🔍 |
punct_comma_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_period_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_semicolon_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_exclamation_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_colon_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_quote_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_question_ratio |
Zheng et al. (2006) Table 3, p.385, no. 88-95 (frequencies of eight marks, this one among them); here the share among all marks | 🔍 |
punct_char_ratio |
de Vel et al. (2001) Table 2, p.60 "Total number of punctuations/C" | 🔍 |
whitespace_ratio |
de Vel et al. (2001) Table 2, p.60 "Total number of white-space characters/C" | 🔍 |
char_a_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_b_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_c_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_d_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_e_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_f_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_g_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_h_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_i_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_j_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_k_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_l_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_m_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_n_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_o_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_p_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_q_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_r_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_s_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_t_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_u_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_v_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_w_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_x_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_y_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
char_z_ratio |
Zheng et al. (2006) Table 3, p.385, no. 7-32 "Frequency of letters (26 features)", A-Z; here each letter of the language's alphabet (Turkish 29, English 26) as a share of all its letters | 🔍 |
Doğrulama adayı olmayanlar¶
61 anahtar. ⚪ olanlar saf tanım (punct_dash_ratio, uppercase_ratio) — adlandırılmış bir literatür ölçüsü değil. ⚫ olanlar bir ölçü değil, dış bir etiket şemasının kategorisini sayıyor; şema kategori tanımlar, ölçüm yayımlamaz. 🔧 olanların formülü bir kaynaktan gelir ama uygulaması bu kütüphaneye aittir. Üçünde de aranacak bir sayı yok.
| Anahtar | Kaynak | Durum |
|---|---|---|
lemma_count |
— | ⚪ |
short_sent_ratio |
This library's threshold calibration (docs/threshold-calibration.md); TR 4, EN 8 — 15th percentile of newspaper columns under the default sentence and word rules. Note: the TR value coincides with Ateşman (1997) p.74, where the easiest text has a mean sentence length of 4 words; that is a text mean, not a threshold, so it is not the source. Calibrated on newspaper columns only | 🔧 |
long_sent_ratio |
This library's threshold calibration (docs/threshold-calibration.md); TR 17, EN 32 — 85th percentile of newspaper columns under the default sentence and word rules. Ateşman's 30 was not used: that is the mean of the hardest text, not a single-sentence threshold (in Turkish newspaper columns 30 words is above the 95th percentile, so as a threshold it would almost never fire). Calibrated on newspaper columns only | 🔧 |
sent_len_entropy |
Shannon (1948) — the entropy formula; applying it to the distribution of sentence lengths is this library's own decision | 🔧 |
pos_noun_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_propn_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_verb_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_adj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_adv_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_det_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_adp_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_intj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_cconj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_sconj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_num_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
pos_aux_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
question_sent_ratio |
— | ⚪ |
sentfinal_noun_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_propn_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_verb_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_adj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_adv_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_det_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_adp_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_intj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_cconj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_sconj_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_num_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_aux_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_pron_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
sentfinal_other_ratio |
de Marneffe et al. (2021) Table 1 (UPOS tag set) | ⚫ |
surface_per_lemma |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
tense_past_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
tense_pres_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
tense_fut_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
aspect_perf_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
aspect_imp_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
aspect_prog_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_nom_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_acc_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_dat_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_loc_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_abl_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
case_gen_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
person_1_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
person_2_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
person_3_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
number_sing_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
number_plur_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
voice_pass_ratio |
de Marneffe et al. (2021) Table 2 (universal morphological features) | ⚫ |
vowel_ratio |
— | ⚪ |
sent_syllable_mean |
— | ⚪ |
polysyllabic_word_ratio |
McLaughlin (1969) p.641; polysyllabic = 3+ syllables — the ratio form of SMOG's input, not the source's own measure | 🔧 |
punct_dash_ratio |
— | ⚪ |
punct_ellipsis_ratio |
— | ⚪ |
punct_paren_ratio |
— | ⚪ |
punct_entropy |
Shannon (1948) — the entropy formula; applying it to the distribution of punctuation types is this library's own decision | 🔧 |
consecutive_punct_ratio |
— | ⚪ |
punct_variety |
— | ⚪ |
uppercase_ratio |
— | ⚪ |
all_caps_word_ratio |
— | ⚪ |
Heceleme — 10/10¶
Heceleme sekiz syllable_* anahtarını ve üç Türkçe okunabilirlik formülünü birden besliyor. Aşağıdaki karşılaştırma sayıyı değil bölütlemeyi sınıyor: yanlış yerden bölünmüş bir sözcük doğru sayıda hece verebilir, sayı karşılaştırması onu yakalamaz.
Kaynak: TDK, "Hece Yapısı ve Satır Sonunda Kelimelerin Bölünmesi" (tdk.gov.tr, 2019).
| Sözcük | TDK | Bizim | Durum |
|---|---|---|---|
| aldı | al-dı |
al-dı |
✅ |
| altlık | alt-lık |
alt-lık |
✅ |
| türkçe | türk-çe |
türk-çe |
✅ |
| program | prog-ram |
prog-ram |
✅ |
| kontrol | kont-rol |
kont-rol |
✅ |
| santral | sant-ral |
sant-ral |
✅ |
| saat | sa-at |
sa-at |
✅ |
| karaosmanoğlu | ka-ra-os-ma-noğ-lu |
ka-ra-os-ma-noğ-lu |
✅ |
| tren | tren |
tren |
✅ |
| strateji | stra-te-ji |
stra-te-ji |
✅ |
Ek — Kincaid Ek A, pasaj bazında¶
Ana tablodaki iki 🟡 satırın (ari, flesch_kincaid_grade) dayandığı 18 karşılaştırma. Ara değerler (vuruş, sözcük) burada duruyor ki fark çıktığında hangi girdiden geldiği görülebilsin.
FRE bandı sütunu ayrı bir kontrol: Tablo 1'in Flesch sütunu 0-100 puanı değil, Flesch'in kendi sınıf bandını basıyor (8-9 = FRE 60-70 gibi). Bizim FRE'miz bandın içine düşüyor mu, ona bakıyor.
Pasaj metinleri tests/veri/kincaid/, ölçüm scripts/kincaid_olcum.py.
| # | Vuruş | Sözcük | ARI kaynak | ARI bizim | Fark | FKGL kaynak | FKGL bizim | Fark | FRE bandı |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 663 | 148 | 10.6 | 10.24 | -0.36 | 9.7 | 9.64 | -0.06 | 8-9 ✅ |
| 2 | 668 | 122 | 20.3 | 16.56 | -3.74 | 16.7 | 15.79 | -0.91 | 16+ ✅ |
| 3 | 684 | 127 | 13.3 | 13.01 | -0.29 | 12.7 | 12.67 | -0.03 | 13-16 ✅ |
| 4 | 749 | 155 | 8.8 | 8.38 | -0.42 | 8.2 | 8.18 | -0.02 | 8-9 ✅ |
| 5 | 517 | 104 | 9.5 | 9.41 | -0.09 | 7.1 | 5.94 | -1.16 | 8-9 ❌ |
| 6 | 685 | 133 | 12.4 | 12.33 | -0.07 | 12.3 | 12.05 | -0.25 | 13-16 ✅ |
| 7 | 1017 | 197 | 12.7 | 12.74 | +0.04 | 11.7 | 11.96 | +0.26 | 13-16 ✅ |
| 8 | 1061 | 197 | 16.4 | 16.25 | -0.15 | 14.7 | 14.98 | +0.28 | 13-16 ✅ |
| 9 | 837 | 181 | 9.7 | 9.40 | -0.30 | 8.0 | 8.16 | +0.16 | 7 ❌ |
| 10 | 1177 | 231 | 13.1 | 12.19 | -0.91 | 11.7 | 11.18 | -0.52 | 13-16 ✅ |
| 11 | 822 | 170 | 7.8 | 7.88 | +0.08 | 8.1 | 7.77 | -0.33 | 8-9 ✅ |
| 12 | 997 | 214 | 16.7 | 15.80 | -0.90 | 11.8 | 7.52 | -4.28 | 10-12 ❌ |
| 13 | 894 | 183 | 13.4 | 13.02 | -0.38 | 10.0 | 10.01 | +0.01 | 10-12 ✅ |
| 14 | 681 | 137 | 12.0 | 11.77 | -0.23 | 12.5 | 12.11 | -0.39 | 13-16 ✅ |
| 15 | 985 | 217 | 9.7 | 8.99 | -0.71 | 8.4 | 8.16 | -0.24 | 8-9 ✅ |
| 16 | 882 | 163 | 13.5 | 13.11 | -0.39 | 13.8 | 14.13 | +0.33 | 16+ ✅ |
| 17 | 1240 | 240 | 10.4 | 9.96 | -0.44 | 9.3 | 8.83 | -0.47 | 10-12 ✅ |
| 18 | 782 | 144 | 10.9 | 10.69 | -0.21 | 6.6 | 6.81 | +0.21 | — |
ARI ortalama mutlak fark 0.54, en büyük 3.74 (pasaj 2). FKGL ortalama mutlak fark 0.55, en büyük 4.28 (pasaj 12). FRE bandının içinde: 14/17.