| --- |
| language: fa |
| tags: |
| - coreference-resolution |
| - persian |
| - zero-pronouns |
| - conllu |
| - corefud |
| - literary |
| license: cc-by-4.0 |
| base_model: ufal/corpipe25-corefud1.3-large-251101 |
| --- |
| |
| # PersianCorefUD-CorPipe |
|
|
| Fine-tuned Persian coreference resolution model based on |
| [CorPipe 25](https://github.com/ufal/corpipe) with a `google/mt5-large` |
| encoder. This is the first coreference model for Persian literary text, |
| trained on the Mehr news corpus and the PersianCorefUD corpus |
| (*The Little Prince* / ุดุงุฒุฏู ฺฉฺูููู). |
|
|
| This model accompanies the paper: |
|
|
| Nassajian, M. (2025). *PersianCorefUD: A Coreference Resolution |
| Corpus for Persian Literary Text*. Manuscript in preparation. |
|
|
| --- |
|
|
| ## Model details |
|
|
| | Property | Value | |
| |---|---| |
| | Base model | `ufal/corpipe25-corefud1.3-large-251101` | |
| | Encoder | `google/mt5-large` | |
| | Training data | Mehr corpus (320 docs) + Little Prince fold 1 (1,005 sentences) | |
| | Optimizer | AdaFactor, lr=2e-5, cosine decay | |
| | Epochs | 60 | |
| | Batch size | 8 | |
| | Sampling exponent | 0.7 | |
|
|
| --- |
|
|
| ## Performance on PersianCorefUD (Little Prince test set) |
|
|
| | System | CoNLL F1 | Zero F1 | |
| |---|---|---| |
| | System 2 โ this model | 52.62% | 0.61% | |
| | System 6 โ this model + rule-based zero linker | 58.70% | 83.30%* | |
|
|
| *Zero F1 for System 6 uses gold zero pronoun node positions. |
| |
| --- |
| |
| ## How to use |
| |
| Your input must be a **CoNLL-U file with Universal Dependencies annotation**. |
| Produce it first with UDPipe 2 using the Persian-PerDT model. |
| |
| **Step 1 โ Get CorPipe 25** |
| ```bash |
| git clone https://github.com/ufal/corpipe |
| cd corpipe |
| pip install -r requirements.txt |
| ``` |
| |
| **Step 2 โ Download this model** |
| ```bash |
| from huggingface_hub import snapshot_download |
| snapshot_download( |
| "Mnsjn/PersianCorefUD-CorPipe", |
| local_dir="persian_coref_model/" |
| ) |
| ``` |
| |
| **Step 3 โ Parse your Persian text with UDPipe first** |
| |
| Go to https://lindat.mff.cuni.cz/services/udpipe/, choose model |
| `persian-perdt`, paste your text, download the CoNLL-U output. |
| |
| **Step 4 โ Run coreference prediction** |
| ```bash |
| python corpipe25.py \ |
| --load persian_coref_model/ \ |
| --test your_file.conllu \ |
| --out your_file_coref.conllu |
| ``` |
| |
| The output is a CoNLL-U file with `Entity=(cXX)` annotations in |
| the MISC column following the CorefUD 1.0 format. |
| |
| --- |
| |
| ## Input format |
| |
| The model expects standard CoNLL-U files. Zero pronoun nodes |
| (empty nodes with decimal IDs like `4.1`) must already be present |
| in the input if you want zero pronoun coreference to be predicted. |
| If you are working with raw text without pre-annotated zero pronouns, |
| the model will still predict coreference for overt mentions. |
| |
| --- |
| |
| ## Corpus |
| |
| The PersianCorefUD corpus used to train and evaluate this model |
| is available at: https://github.com/Mnsjn/PersianCorefUD |
| |
| --- |
| |
| ## Citation |
| |
