Datasets:

Tasks: other
Task Categories: text-scoring
Languages: en
Multilinguality: monolingual
Size Categories: 10K<n<100K
Annotations Creators: crowdsourced
Source Datasets: extended

Dataset Card Creation Guide

Dataset Summary

Google's query wellformedness dataset was created by crowdsourcing well-formedness annotations for 25,100 queries from the Paralex corpus. Every query was annotated by five raters each with 1/0 rating of whether or not the query is well-formed.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

English

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

  • rating: a float between 0-1
  • sentence: query which you want to rate

Data Splits

Train Valid Test
Input Sentences 17500 3750 3850

Dataset Creation

Curation Rationale

Understanding search queries is a hard problem as it involves dealing with “word salad” text ubiquitously issued by users. However, if a query resembles a well-formed question, a natural language processing pipeline is able to perform more accurate interpretation, thus reducing downstream compounding errors. Hence, identifying whether or not a query is well formed can enhance query understanding. This dataset introduce a new task of identifying a well-formed natural language question.

Source Data

Used the Paralex corpus (Fader et al., 2013) that contains pairs of noisy paraphrase questions. These questions were issued by users in WikiAnswers (a Question-Answer forum) and consist of both web-search query like constructs (“5 parts of chloroplast?”) and well-formed questions (“What is the punishment for grand theft?”).

Initial Data Collection and Normalization

Selected 25,100 queries from the unique list of queries extracted from the corpus such that no two queries in the selected set are paraphrases.

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

The queries are annotated into well-formed or non-wellformed questions if it satisfies the following:

  1. Query is grammatical.
  2. Query is an explicit question.
  3. Query does not contain spelling errors.

Who are the annotators?

Every query was labeled by five different crowdworkers with a binary label indicating whether a query is well-formed or not. And average of the ratings of the five annotators was reported, to get the probability of a query being well-formed.

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

Query-wellformedness dataset is licensed under CC BY-SA 4.0. Any third party content or data is provided “As Is” without any warranty, express or implied.

Citation Information

@InProceedings{FaruquiDas2018,
   title = {{Identifying Well-formed Natural Language Questions}},
   author = {Faruqui, Manaal and Das, Dipanjan},
   booktitle = {Proc. of EMNLP},
   year = {2018}
}

Contributions

Thanks to @vasudevgupta7 for adding this dataset.

Models trained or fine-tuned on google_wellformed_query