README.md

metadata

language:
  - tg
license: apache-2.0
tags:
  - morphological-corpus
  - tajik
  - grammar
  - linguistic

Tajik Unified Morphological Corpus

Author: Arabov Mullosharaf Kurbonovich

Morphological corpus of the Tajik language, combining data from tajik-corpus.org.
Contains wordforms, lemmas, grammatical tags, and frequency information.

📖 Description

The dataset includes 200,144 entries (wordforms with their morphological analyses) with:

• wordform (word)
• lemma (base form)
• grammar tag (grammar) - combines POS and grammatical features
• part of speech (pos)
• grammatical features (features)
• gloss (short meaning)
• English translation (trans_en)
• Russian translation (trans_ru)
• raw grammar tag (gramm_raw)
• frequency (freq) - number of occurrences in the corpus

📊 Statistics

Metric	Value
Total entries	200,144
Unique wordforms	135,595
Unique lemmas	20,618
Unique grammar tags	10,287
Total frequency sum	200,144
Mean frequency per entry	1.0
Median frequency	1.0

Part of Speech Distribution

Part of Speech	Count
N	126,907
ADJ	44,995
V	21,501
ADV	3,975
PRON	886
NUM	774
CONJ	383
INTJ	300
PRTCL	285
PREP	92
part	31
POST	11
INTZ	3
PROP	1

Most Frequent Words

Word	Frequency
бозоргонам	12
бозоргоне	12
бозоргонеро	12
бозӣ	12
баротӣ	11
баротам	10
баҳодурӣ	10
бозорам	10
бозоре	10
бозореро	10

Most Frequent Lemmas

Lemma	Frequency
сар	276
бар	267
овардан	226
ёфтан	223
кардан	215
гуфтан	202
боз	201
додан	194
кор	194
омадан	193

Most Frequent Grammar Tags

Grammar Tag	Count
N,sg	9,077
N,sg,ezf	7,579
N,and	5,502
N,sg,and	5,502
ADJ,sg	4,589
N,sg,obj.def	3,441
ADJ,sg,ezf	3,221
N,sg,indef	2,995
N,sg,rel	2,995
N,pl,ezf	2,783

Word Length Statistics (in characters)

Statistic	Characters
Mean	8
Median	8
Minimum	1
Maximum	21

Number of Grammatical Features per Wordform

Statistic	Number of Tags
Mean	4.6
Median	4
Minimum	1
Maximum	15

🚀 Usage Example

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("TajikNLPWorld/TajikUnifiedCorpus")
train = dataset["train"]

# Filter nouns
nouns = train.filter(lambda x: x["pos"] == "N")

# Filter verbs in past tense
verbs_past = train.filter(lambda x: "past" in x["features"] if x["features"] else False)

# Top 10 most frequent words
import pandas as pd
df = train.to_pandas()
top_words = df.groupby("word")["freq"].sum().nlargest(10)
print(top_words)

# Iterate through records
for record in train.select(range(5)):
    print(f"{record['word']} -> {record['lemma']} ({record['grammar']})")

🔬 Possible Applications

• Morphological analysis of Tajik language
• Part-of-speech tagging training
• Linguistic research
• Dictionary and educational material creation
• Grammatical pattern extraction
• Machine translation systems

📜 Citation

If you use this dataset in your research, please cite:

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

📜 License

Apache 2.0