Tajik Morphological Corpus
A morphological corpus of the Tajik language containing word forms, lemmas, grammatical tags, and frequency information.
๐ 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) โ number of occurrences in the original corpus
๐ 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 |
| ะธะฝ |
714,184 |
| ะฑะฐัะพะธ |
315,952 |
| ะฐัั |
303,700 |
| ัะพ |
191,645 |
| ะพะฝาณะพ |
144,608 |
| ะฑะฐั |
106,422 |
| าณะฐะผะธะฝ |
79,441 |
| ัั |
77,709 |
| ะฝะตัั |
59,390 |
| ะฟะฐั |
55,807 |
Most frequent lemmas
| Lemma |
Frequency |
| ะธะฝ |
724,582 |
| ะฐัั |
322,903 |
| ะฑะฐัะพะธ |
319,891 |
| ัะฐ/ัะพ |
191,645 |
| ะพะฝ |
188,309 |
| ะฑะฐั/ะฑััะดะฐะฝ |
106,422 |
| าณะฐะผ/าณะฐะผะธะฝ |
80,561 |
| ัั |
77,796 |
| ะฝะต/ะฝะตัั |
59,391 |
| ะฟะฐั |
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 |
๐ Usage example
from datasets import load_dataset
dataset = load_dataset("TajikNLPWorld/TajikMorphCorpus")
train = dataset["train"]
nouns = train.filter(lambda x: "N" in x["grammar"])
top_words = train.to_pandas().groupby("word")["freq"].sum().nlargest(10)
for record in train:
print(record["word"], record["lemma"], record["grammar"], record["freq"])
๐ฌ Potential applications
- Morphological analysis of Tajik
- Training partโofโspeech taggers
- Linguistic research on grammatical categories
- Creating dictionaries and teaching materials
๐ License
Apache 2.0
๐ค 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}
}