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metadata
license: apache-2.0
dataset_info:
  - config_name: mmc_en
    features:
      - name: doc_name
        dtype: string
      - name: sentences
        sequence:
          sequence:
            sequence: string
      - name: coref_chains
        sequence:
          sequence:
            sequence: int64
    splits:
      - name: train
        num_bytes: 28164357
        num_examples: 955
      - name: dev
        num_bytes: 4043571
        num_examples: 134
      - name: test
        num_bytes: 3103262
        num_examples: 133
    download_size: 3609139
    dataset_size: 35311190
  - config_name: mmc_fa
    features:
      - name: doc_name
        dtype: string
      - name: sentences
        sequence:
          sequence:
            sequence: string
      - name: coref_chains
        sequence:
          sequence:
            sequence: int64
    splits:
      - name: train
        num_bytes: 22553374
        num_examples: 950
      - name: dev
        num_bytes: 3579538
        num_examples: 134
      - name: test
        num_bytes: 2480699
        num_examples: 133
    download_size: 2969009
    dataset_size: 28613611
  - config_name: mmc_fa_corrected
    features:
      - name: doc_name
        dtype: string
      - name: sentences
        sequence:
          sequence:
            sequence: string
      - name: coref_chains
        sequence:
          sequence:
            sequence: int64
    splits:
      - name: train
        num_bytes: 22553374
        num_examples: 950
      - name: dev
        num_bytes: 3579538
        num_examples: 134
      - name: test
        num_bytes: 2512884
        num_examples: 133
    download_size: 2975807
    dataset_size: 28645796
  - config_name: mmc_zh_corrected
    features:
      - name: doc_name
        dtype: string
      - name: sentences
        sequence:
          sequence:
            sequence: string
      - name: coref_chains
        sequence:
          sequence:
            sequence: int64
    splits:
      - name: train
        num_bytes: 29749762
        num_examples: 948
      - name: dev
        num_bytes: 4442503
        num_examples: 134
      - name: test
        num_bytes: 2240351
        num_examples: 133
    download_size: 3416567
    dataset_size: 36432616
  - config_name: mmc_zh_uncorrected
    features:
      - name: doc_name
        dtype: string
      - name: sentences
        sequence:
          sequence:
            sequence: string
      - name: coref_chains
        sequence:
          sequence:
            sequence: int64
    splits:
      - name: train
        num_bytes: 29749762
        num_examples: 948
      - name: dev
        num_bytes: 4442503
        num_examples: 134
      - name: test
        num_bytes: 3373346
        num_examples: 133
    download_size: 3457199
    dataset_size: 37565611
configs:
  - config_name: mmc_en
    data_files:
      - split: train
        path: mmc_en/train-*
      - split: dev
        path: mmc_en/dev-*
      - split: test
        path: mmc_en/test-*
  - config_name: mmc_fa
    data_files:
      - split: train
        path: mmc_fa/train-*
      - split: dev
        path: mmc_fa/dev-*
      - split: test
        path: mmc_fa/test-*
  - config_name: mmc_fa_corrected
    data_files:
      - split: train
        path: mmc_fa_corrected/train-*
      - split: dev
        path: mmc_fa_corrected/dev-*
      - split: test
        path: mmc_fa_corrected/test-*
  - config_name: mmc_zh_corrected
    data_files:
      - split: train
        path: mmc_zh_corrected/train-*
      - split: dev
        path: mmc_zh_corrected/dev-*
      - split: test
        path: mmc_zh_corrected/test-*
  - config_name: mmc_zh_uncorrected
    data_files:
      - split: train
        path: mmc_zh_uncorrected/train-*
      - split: dev
        path: mmc_zh_uncorrected/dev-*
      - split: test
        path: mmc_zh_uncorrected/test-*

MMC (Multilingual Multiparty Coreference)

Details

Data for the paper "Multilingual Coreference Resolution in Multiparty Dialogue" TACL 2023

Citation

@article{zheng-etal-2023-multilingual,
    title = "Multilingual Coreference Resolution in Multiparty Dialogue",
    author = "Zheng, Boyuan  and
      Xia, Patrick  and
      Yarmohammadi, Mahsa  and
      Van Durme, Benjamin",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "11",
    year = "2023",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://aclanthology.org/2023.tacl-1.52",
    doi = "10.1162/tacl_a_00581",
    pages = "922--940",
    abstract = "Existing multiparty dialogue datasets for entity coreference resolution are nascent, and many challenges are still unaddressed. We create a large-scale dataset, Multilingual Multiparty Coref (MMC), for this task based on TV transcripts. Due to the availability of gold-quality subtitles in multiple languages, we propose reusing the annotations to create silver coreference resolution data in other languages (Chinese and Farsi) via annotation projection. On the gold (English) data, off-the-shelf models perform relatively poorly on MMC, suggesting that MMC has broader coverage of multiparty coreference than prior datasets. On the silver data, we find success both using it for data augmentation and training from scratch, which effectively simulates the zero-shot cross-lingual setting.",
}