README.md

metadata

language:
  - tg
license: apache-2.0
tags:
  - morphological-corpus
  - tajik
  - grammar
  - linguistic
pretty_name: Tajik Morphological Corpus

Tajik Morphological Corpus

A morphological corpus of the Tajik language containing word forms, lemmas, grammatical tags, and frequency information.

📖 Description

The dataset includes 3,609 unique word forms (after deduplication) with:

• word form (word)
• lemma (lemma)
• grammatical tags (grammar), separated by commas and a vertical bar for alternative analyses
• frequency (freq) – number of occurrences in the original corpus

📊 Statistics

Metric	Value
Total entries	3,609
Unique word forms	3,460
Unique lemmas	2,126
Unique grammar tags	1,988
Total frequency	2,820,977
Average frequency per entry	781.7
Median frequency	3.0

Most frequent words

Word	Frequency
ин	714,184
барои	315,952
аст	303,700
то	191,645
онҳо	144,608
бар	106,422
ҳамин	79,441
ту	77,709
нест	59,390
пас	55,807

Most frequent lemmas

Lemma	Frequency
ин	724,582
аст	322,903
барои	319,891
та/то	191,645
он	188,309
бар/бурдан	106,422
ҳам/ҳамин	80,561
ту	77,796
не/нест	59,391
пас	55,823

Most frequent grammar tags

Grammar tag	Count
cnject2, indir, prs, 2, sg, V	part, part.mod.prs, part.mod, V
hab.part.pst, part, sbjv.hab, V	42
inf, prs, 2, sg, V, cop, cop.encl	part, part.fut, V
pst, fut, 3, sg, V	30
pass.part, part.pst, pass.part.pst, part, V	28
part, part.prs, V	27
indir, imp, 2, neg, neg2, sg, V	27
part.pst, part, pluprf, V	26
part.pst, part, pst.prog, prog, V	26
part.pst, part, sbjv.pst, V	24

Word length (characters)

Statistic	Characters
Mean	8.4
Median	8
Minimum	2
Maximum	18

Number of grammar tags per word form

Statistic	Number of tags
Mean	8.1
Median	6
Minimum	1
Maximum	59

🚀 Usage example

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("TajikNLPWorld/TajikMorphCorpus")

# Access the train split
train = dataset["train"]

# Find all nouns (tag contains "N")
nouns = train.filter(lambda x: "N" in x["grammar"])

# Top 10 most frequent words
top_words = train.to_pandas().groupby("word")["freq"].sum().nlargest(10)

# Iterate through records
for record in train:
    print(record["word"], record["lemma"], record["grammar"], record["freq"])

🔬 Potential applications

• Morphological analysis of Tajik
• Training part‑of‑speech taggers
• Linguistic research on grammatical categories
• Creating dictionaries and teaching materials

📜 License

Apache 2.0

🤝 Citation

If you use this dataset, please cite:

@dataset{tajik_morph_corpus_2026,
    title = {Tajik Morphological Corpus},
    author = {Arabov Mullosharaf Kurbonovich (TajikNLPWorld)},
    year = {2026},
    publisher = {Hugging Face},
    url = {https://huggingface.co/datasets/TajikNLPWorld/TajikMorphCorpus}
}