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metadata
license: mit
language:
  - en
language_creators:
  - crowdsourced
multilinguality:
  - monolingual
pretty_name: NevIR
size_categories:
  - 1K<n<10K
tags:
  - negation
  - information_retrieval
  - IR

Dataset Card for NevIR: Negation in Neural Information Retrieval

Dataset Description

Dataset Summary

Data from the paper: "NevIR: Negation in Neural Information Retrieval".

If you use this dataset, we would appreciate you citing our work:

@inproceedings{weller-et-al-2023-nevir,
  title={NevIR: Negation in Neural Information Retrieval},
  author={Weller, Orion and Lawrie, Dawn, and Van Durme, Benjamin},
  proceedings={arxiv},
  year={2023}
}

From the paper: "We introduce CondaQA to facilitate the future development of models that can process negation effectively. This is the first English reading comprehension dataset which requires reasoning about the implications of negated statements in paragraphs. We collect paragraphs with diverse negation cues, then have crowdworkers ask questions about the implications of the negated statement in the passage. We also have workers make three kinds of edits to the passage---paraphrasing the negated statement, changing the scope of the negation, and reversing the negation---resulting in clusters of question-answer pairs that are difficult for models to answer with spurious shortcuts. CondaQA features 14,182 question-answer pairs with over 200 unique negation cues."

Supported Tasks and Leaderboards

The task is to answer a question given a Wikipedia passage that includes something being negated. There is no official leaderboard.

Language

English

Dataset Structure

Data Instances

Here's an example instance:

{"QuestionID": "q10", 
"original cue": "rarely", 
"PassageEditID": 0, 
"original passage": "Drug possession is the crime of having one or more illegal drugs in one's possession, either for personal use, distribution, sale or otherwise. Illegal drugs fall into different categories and sentences vary depending on the amount, type of drug, circumstances, and jurisdiction. In the U.S., the penalty for illegal drug possession and sale can vary from a small fine to a prison sentence. In some states, marijuana possession is considered to be a petty offense, with the penalty being comparable to that of a speeding violation. In some municipalities, possessing a small quantity of marijuana in one's own home is not punishable at all. Generally, however, drug possession is an arrestable offense, although first-time offenders rarely serve jail time. Federal law makes even possession of \"soft drugs\", such as cannabis, illegal, though some local governments have laws contradicting federal laws.", 
"SampleID": 5294, 
"label": "YES", 
"original sentence": "Generally, however, drug possession is an arrestable offense, although first-time offenders rarely serve jail time.", 
"sentence2": "If a drug addict is caught with marijuana, is there a chance he will be jailed?", 
"PassageID": 444, 
"sentence1": "Drug possession is the crime of having one or more illegal drugs in one's possession, either for personal use, distribution, sale or otherwise. Illegal drugs fall into different categories and sentences vary depending on the amount, type of drug, circumstances, and jurisdiction. In the U.S., the penalty for illegal drug possession and sale can vary from a small fine to a prison sentence. In some states, marijuana possession is considered to be a petty offense, with the penalty being comparable to that of a speeding violation. In some municipalities, possessing a small quantity of marijuana in one's own home is not punishable at all. Generally, however, drug possession is an arrestable offense, although first-time offenders rarely serve jail time. Federal law makes even possession of \"soft drugs\", such as cannabis, illegal, though some local governments have laws contradicting federal laws."
}

Data Fields

  • QuestionID: unique ID for this question (might be asked for multiple passages)
  • original cue: Negation cue that was used to select this passage from Wikipedia
  • PassageEditID: 0 = original passage, 1 = paraphrase-edit passage, 2 = scope-edit passage, 3 = affirmative-edit passage
  • original passage: Original Wikipedia passage the passage is based on (note that the passage might either be the original Wikipedia passage itself, or an edit based on it)
  • SampleID: unique ID for this passage-question pair
  • label: answer
  • original sentence: Sentence that contains the negated statement
  • sentence2: question
  • PassageID: unique ID for the Wikipedia passage
  • sentence1: passage

Data Splits

Data splits can be accessed as:

from datasets import load_dataset
train_set = load_dataset("nevir", "train")
dev_set = load_dataset("nevir", "dev")
test_set = load_dataset("nevir", "test")

Dataset Creation

Full details are in the paper.