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# Dataset Card for
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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## Dataset Description
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- **Homepage:**
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- **Repository:**
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- **Paper:**
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- **Leaderboard:**
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- **Point of Contact:**
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### Dataset Summary
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### Supported Tasks and Leaderboards
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### Languages
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## Dataset Structure
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### Data Instances
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### Data Fields
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### Data Splits
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## Dataset Creation
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task_ids: []
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# Dataset Card for "PiC: Phrase Sense Disambiguation"
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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## Dataset Description
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- **Homepage:** [https://phrase-in-context.github.io/](https://phrase-in-context.github.io/)
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- **Repository:** [https://github.com/phrase-in-context](https://github.com/phrase-in-context)
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- **Paper:**
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- **Leaderboard:**
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- **Point of Contact:** [Thang Pham](<[email protected]>)
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- **Size of downloaded dataset files:** 49.95 MB
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- **Size of the generated dataset:** 43.26 MB
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- **Total amount of disk used:** 93.20 MB
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### Dataset Summary
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PSD is a phrase retrieval task like PR-pass and PR-page but more challenging since each example contains two short paragraphs (~11 sentences each) which trigger different senses of the same phrase.
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The goal is to find the instance of the target phrase **t** that is semantically similar to a paraphrase **q**
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We propose to use the train & dev sets of PR and 5,150 PSD examples for testing.
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<p align="center">
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![PSD_sample](https://auburn.edu/~tmp0038/PiC/psd_sample.png "PSD sample")
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</p>
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### Supported Tasks and Leaderboards
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### Languages
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English.
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## Dataset Structure
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### Data Instances
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**PSD**
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* Size of downloaded dataset files: 49.95 MB
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* Size of the generated dataset: 43.26 MB
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* Total amount of disk used: 93.20 MB
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An example of 'test' looks as follows.
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```
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{
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"id": "297-1",
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"title": "https://en.wikipedia.org/wiki?curid=2226019,https://en.wikipedia.org/wiki?curid=1191780",
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"context": "In addition, the results from the study did not support the idea of females preferring complexity over simplicity in song sequences. These findings differ from past examinations, like the 2008 Morisake et al. study that suggested evidence of female Bengalese finches preferring complex songs over simple ones. Evolutionary adaptations of specifically complex song production in relation to female preference in Bengalese finches continues to be a topic worth examining. Comparison with zebra finches. Bengalese finches and zebra finches are members of the estrildiae family and are age-limited learners when it comes to song learning and the acoustic characteristics of their songs (Peng et al., 2012). Both of these species have been widely used in song learning based animal behavior research and although they share many characteristics researchers have been able to determine stark differences between the two. Previous to research done in 1987, it was thought that song learning in Bengalese finches was similar to zebra finches but there was no research to support this idea. Both species require learning from an adult during a sensitive juvenile phase in order to learn the species specific and sexually dimorphic songs. This tutor can be the father of the young or other adult males that are present around the juvenile. Clayton aimed to directly compare the song learning ability of both of these species to determine if they have separate learning behaviors. Many students find they can not possibly complete all the work assigned them; they learn to neglect some of it. Some student groups maintain files of past examinations which only worsen this situation. The difference between the formal and real requirements produced considerable dissonance among the students and resulted in cynicism, scorn, and hypocrisy among students, and particular difficulty for minority students. No part of the university community, writes Snyder, neither the professors, the administration nor the students, desires the end result created by this process. The \"Saturday Review\" said the book \"will gain recognition as one of the more cogent 'college unrest' books\" and that it presents a \"most provocative thesis.\" The book has been cited many times in studies. References. [[Category:Curricula]] [[Category:Philosophy of education]] [[Category:Massachusetts Institute of Technology]] [[Category:Books about social psychology]] [[Category:Student culture]] [[Category:Books about education]] [[Category:1970 non-fiction books]]",
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"query": "previous exams",
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"answers": {
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"text": ["past examinations"],
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"answer_start": [1621]
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}
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}
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```
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### Data Fields
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The data fields are the same among all subsets and splits.
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* id: a string feature.
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* title: a string feature.
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* context: a string feature.
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* question: a string feature.
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* answers: a dictionary feature containing:
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* text: a list of string features.
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* answer_start: a list of int32 features.
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### Data Splits
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| name |train|validation|test|
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|--------------------|----:|---------:|---:|
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|PSD |20002| 3000|5000|
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## Dataset Creation
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