The CoreSearch Dataset

A large-scale dataset for cross-document event coreference search

Paper: Cross-document Event Coreference Search: Task, Dataset and Modeling
CoreSearchV2: A cleaner version of this dataset is now available at https://huggingface.co/datasets/biu-nlp/CoreSearchV2

Languages

English

Load Dataset

You can read/download the dataset files following Huggingface Hub instructions.
For example, below code will load CoreSearch DPR folder:

from huggingface_hub import hf_hub_url, cached_download
import json
REPO_ID = "datasets/Intel/CoreSearch"
DPR_FILES = "/dpr/"

dpr_files = ["dpr/Dev.json", "dpr/Train.json", "dpr/Test.json"]

dpr_jsons = list()
for _file in dpr_files:
    dpr_jsons.append(json.load(open(cached_download(
        hf_hub_url(REPO_ID, _file)), "r")))

Data Splits

Final version of the CD event coreference search dataset
| | Train | Valid | Test | Total |

| ----- | ------ | ----- | ---- | ---- | | WEC-Eng Validated Data | | | | | | # Clusters | 237 | 49 | 236 | 522 | | # Passages (with Mentions) | 1,503 | 341 | 1,266 | 3,110 | | # Added Destructor Passages | 922,736 | 923,376 | 923,746 | 2,769,858 | | # Total Passages | 924,239 | 923,717 | 925,012 | 2,772,968 |

Citation

@inproceedings{eirew-etal-2022-cross,
    title = "Cross-document Event Coreference Search: Task, Dataset and Modeling",
    author = "Eirew, Alon  and
      Caciularu, Avi  and
      Dagan, Ido",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.emnlp-main.58",
    pages = "900--913",
    abstract = "The task of Cross-document Coreference Resolution has been traditionally formulated as requiring to identify all coreference links across a given set of documents. We propose an appealing, and often more applicable, complementary set up for the task {--} Cross-document Coreference Search, focusing in this paper on event coreference. Concretely, given a mention in context of an event of interest, considered as a query, the task is to find all coreferring mentions for the query event in a large document collection. To support research on this task, we create a corresponding dataset, which is derived from Wikipedia while leveraging annotations in the available Wikipedia Event Coreferecene dataset (WEC-Eng). Observing that the coreference search setup is largely analogous to the setting of Open Domain Question Answering, we adapt the prominent Deep Passage Retrieval (DPR) model to our setting, as an appealing baseline. Finally, we present a novel model that integrates a powerful coreference scoring scheme into the DPR architecture, yielding improved performance.",
}

License

We provide the following data sets under a Creative Commons Attribution-ShareAlike 3.0 Unported License. It is based on content extracted from Wikipedia that is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License

Contact

If you have any questions please create a Github issue at https://github.com/AlonEirew/CoreSearch.