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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

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