Update README.md

## About the dataset

RAW-C contains relatedness judgments about ambiguous words in minimal pair contexts, e.g., "She liked the marinated *lamb*" vs. "She liked the friendly *lamb*". The dataset was originally published in [ACL 2021](https://aclanthology.org/2021.acl-long.550/).

- 672 sentence pairs total.
- 112 words (2 senses each, 2 sentences per sense).
- Each sentence pair is hand-annotated for whether they belong to the **Same Sense** or **Different Sense**, and whether the relation is one of **Polysemy** or **Homonymy**.

## Navigating the dataset

The complete set of sentence pairs with relatedness judgments can be found in `raw-c.csv`. Key columns:

- `word`
- sentence1 and sentence2: the sentence pair being contrasted
- `same`: whether the target word has the same or different meaning across the sentence pair
- `ambiguity_type`: whether the different-sense use is Polysemy or Homonymy
- `mean_relatedness`: the mean relatedness judgment across human participants
- `string`: the actual target word that occurs in the sentence (e.g., "break" vs. "broke").

This file also contains information about the number of annotators who rated each sentence pair (`count`), as well as the variance across those judgments (`sd_relatedness`).

We also include `raw-c_with_dominance.csv`, which contains all of the same columns as RAW-C, along with human annotations for the relative **dominance** of the distinct meanings:

- `dominance_sentence2: mean dominance of sentence2 relative to sentence1.
- `sd_dominance_sentence2: standard deviation for dominance judgments of sentence2 relative to sentence1.

*Note that dominance judgments are only included for Different Sense sentence pairs.*

## Citation

APA:

```
Trott, S., Bergen, B. (2021). RAW-C: Relatedness of Ambiguous Words––in Context (A New Lexical Resource for English). Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021).
```

BibTex:

```
@inproceedings{trott-bergen-2021-raw,
title = "{RAW}-{C}: Relatedness of Ambiguous Words in Context (A New Lexical Resource for {E}nglish)",
author = "Trott, Sean and
Bergen, Benjamin",
editor = "Zong, Chengqing and
Xia, Fei and
Li, Wenjie and
Navigli, Roberto",
booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.acl-long.550/",
doi = "10.18653/v1/2021.acl-long.550",
pages = "7077--7087",
abstract = "Most words are ambiguous{---}-i.e., they convey distinct meanings in different contexts{---}-and even the meanings of unambiguous words are context-dependent. Both phenomena present a challenge for NLP. Recently, the advent of contextualized word embeddings has led to success on tasks involving lexical ambiguity, such as Word Sense Disambiguation. However, there are few tasks that directly evaluate how well these contextualized embeddings accommodate the more continuous, dynamic nature of word meaning{---}-particularly in a way that matches human intuitions. We introduce RAW-C, a dataset of graded, human relatedness judgments for 112 ambiguous words in context (with 672 sentence pairs total), as well as human estimates of sense dominance. The average inter-annotator agreement (assessed using a leave-one-annotator-out method) was 0.79. We then show that a measure of cosine distance, computed using contextualized embeddings from BERT and ELMo, correlates with human judgments, but that cosine distance also systematically underestimates how similar humans find uses of the same sense of a word to be, and systematically overestimates how similar humans find uses of different-sense homonyms. Finally, we propose a synthesis between psycholinguistic theories of the mental lexicon and computational models of lexical semantics."
```

README.md

@@ -1,3 +1,10 @@
----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+language:
+- en
+tags:
+- ambiguity
+- relatedness
+- language
+pretty_name: Relatedness of Ambiguous Words——in Context (RAW-C)
+---