Rename pair_id to target_index and document it as WiC-style target word positions

README.md

@@ -70,8 +70,8 @@ The label distribution is exactly balanced.
 |---|---|---|
 | `id` | int | Row index (0-based). |
 | `word` | string | Target word (one of 20 nouns). |
-| `pair_id` | string | Instance identifier carried over from the CoarseWSD-20 conversion (format `x-y`). |
-| `sentence1` | string | First context. Tokenised, lower-cased text from CoarseWSD-20 (Wikipedia). |
+| `target_index` | string | Position of the target word in `sentence1` and `sentence2`, as `index1-index2`. Indices are 0-based and count whitespace-separated tokens, following the original WiC data format. |
+| `sentence1` | string | First context: a sentence from CoarseWSD-20, whose text comes from Wikipedia. Text is lower-cased and pre-tokenised, with tokens separated by single spaces. |
 | `sentence2` | string | Second context. |
 | `label` | string | `"True"` if the target word has the same coarse sense in both sentences, else `"False"`. |
 
@@ -104,7 +104,7 @@ Per-word statistics (from the paper, Table 8):
 Example:
 
 ```json
-{"word": "apple", "pair_id": "6-18",
+{"word": "apple", "target_index": "6-18",
  "sentence1": "the local economy includes forestry , apple orchard and sheep and dairy farming .",
  "sentence2": "symbol is one of the four standard fonts available on all postscript - based printers , starting with apple 's original laserwriter ( 1985 ) .",
  "label": "False"}
@@ -145,7 +145,7 @@ Example:
 ```
 data/coarse_grained/test.jsonl   # 2,798 rows
 data/fine_grained/test.jsonl     # 1,185 rows
-raw/coarse_grained_WiC.tsv       # original release file, no header: word, pair_id, sentence1, sentence2, label
+raw/coarse_grained_WiC.tsv       # original release file, no header: word, target_index, sentence1, sentence2, label
 raw/fine_grained_WiC.tsv         # original release file, with header; labels are T / F
 ```
 
@@ -156,8 +156,10 @@ The raw TSV files are the original release files and are otherwise unchanged.
 ## Notes
 
 - Sentences in `coarse_grained` are lower-cased and tokenised (punctuation separated by spaces), as in CoarseWSD-20.
-- `coarse_grained` contains one exact duplicate pair (`bank`, `pair_id` `12-5`). It is kept so that the
+- `coarse_grained` contains one exact duplicate pair (`bank`, `target_index` `12-5`). It is kept so that the
   counts match the paper.
+- In `coarse_grained`, `target_index` points at the target word in 2,797 of 2,798 rows. In one `club` row
+  (`target_index` `85-19`) the first index is off because of a tokenisation irregularity in the source sentence.
 - These are evaluation sets. There is no training split.
 
 ## Source datasets