Indiscriminate Identity Coreference
Collection
Datasets transformed into indiscriminate clustering of continuous textual spans. • 15 items • Updated • 1
sentences listlengths 1 94 | coref_chains sequencelengths 0 136 | id stringlengths 10 10 | text stringlengths 24 4.56k | genre stringclasses 2
values | meta_data dict |
|---|---|---|---|---|---|
[
{
"id": 1,
"misc": {
"parse_tree": "(ROOT (S (SBAR (IN If) (S (NP (DT a) (NN photon)) (VP (VP (VBZ is) (VP (VBN directed) (PP (IN through) (NP (DT a) (NN plane))) (PP (IN with) (NP (NP (CD two) (NNS slits)) (PP (IN in) (NP (PRP it))))))) (CC and) (VP (CC either)) (VP (VBZ is) (VP (VBN observed)))))) (... | [
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... | s01e01c00t | If a photon is directed through a plane with two slits in it and either is observed it will not go through both . If unobserved, it will . If it's observed after it left the plane, before it hits its target...it will not have gone through both slits. Agreed . What's your point? There's no point, I just think it's a goo... | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[
{
"id": 1,
"misc": {
"parse_tree": "(ROOT (SQ (VBP Are) (NP (PRP you)) (ADVP (RB still)) (ADJP (JJ mad) (PP (IN about) (NP (DT the) (NN sperm) (NN bank)))) (. ?)))"
},
"speaker": "Sheldon",
"text": "Are you still mad about the sperm bank?",
"tokens": [
{
"deprel": "cop",
... | [
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... | s01e01c01t | Are you still mad about the sperm bank? No. You wanna hear an interesting thing about stairs? Not really. If the height of a step is off by as little as two millimeters...most people will trip. I don't care . Two millime ...? That doesn't seem right. It's true . I did a series of experiments when I was 12 . My father b... | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[{"id":1,"misc":{"parse_tree":"(ROOT (S (S (ADVP (DT All) (RB right)) (, ,) (NP (EX there)) (NP (PRP(...TRUNCATED) | [[[0,4,4],[0,7,7]],[[0,10,10],[3,2,2],[3,0,2],[5,7,7],[6,5,5],[6,9,9],[7,4,4],[8,2,2],[9,10,11]],[[2(...TRUNCATED) | s01e01c03t | "All right, there it goes . It sticks, I'm sorry. Okay, thanks. You're welcome . Oh, you're just gon(...TRUNCATED) | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[{"id":1,"misc":{"parse_tree":"(ROOT (S (NP (PRP I)) (ADVP (RB really)) (VP (VBP think) (SBAR (S (NP(...TRUNCATED) | [[[0,0,0],[3,9,9],[7,7,7],[8,0,0],[9,3,3],[10,2,2],[15,2,2]],[[0,3,3]],[[0,6,7]],[[0,9,9]],[[1,1,1],(...TRUNCATED) | s01e01c04t | "I really think we should examine the chain of causality here. Must we? Event A: A beautiful woman s(...TRUNCATED) | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[{"id":1,"misc":{"parse_tree":"(ROOT (S (RB So) (NP (PRP you) (NNS guys)) (VP (VBP work) (PP (IN wit(...TRUNCATED) | [[[0,1,1]],[[0,1,2],[1,5,5],[2,2,2],[2,6,6],[4,0,0],[4,4,5],[4,2,5]],[[0,5,5]],[[0,7,7]],[[0,5,7]],[(...TRUNCATED) | s01e01c05t | "So you guys work with Leonard and Sheldon at the university? I'm sorry, do you speak English? Oh, h(...TRUNCATED) | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[{"id":1,"misc":{"parse_tree":"(ROOT (S (NP (PRP I)) (VP (MD 'll) (VP (VB do) (NP (DT the) (NN talki(...TRUNCATED) | [[[0,0,0],[2,2,2],[2,4,4],[4,2,2],[8,0,0],[9,1,1],[9,11,11],[10,5,5],[11,7,7],[13,2,2]],[[0,3,4]],[[(...TRUNCATED) | s01e01c06t | "I'll do the talking. Yeah? Hi . I'm Leonard, this is Sheldon. Hello. What did I just ...? We're her(...TRUNCATED) | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[{"id":1,"misc":{"parse_tree":"(ROOT (S (S (NP (DT This)) (VP (VBZ is) (NP (PRP it)))) (. .) (S (NP (...TRUNCATED) | [[[0,0,0],[0,2,2]],[[0,4,4],[3,0,0],[3,2,2]],[[0,7,8]],[[1,3,3],[3,4,4],[3,6,6]],[[1,7,8]],[[4,1,2]](...TRUNCATED) | s01e01c07t | "This is it . I'll do the talking. Good thinking, I'll just be the muscle. Yeah? I'm Leonard, this i(...TRUNCATED) | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[{"id":1,"misc":{"parse_tree":"(ROOT (NP (NNP Leonard) (. .)))"},"speaker":"Sheldon","text":"Leonard(...TRUNCATED) | [
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... | s01e01c08t | Leonard. What? My mom bought me those pants. I ’m sorry. You're gonna have to call her. | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[{"id":1,"misc":{"parse_tree":"(ROOT (S (NP (NNP Sheldon)) (, ,) (NP (PRP I)) (VP (VBP am) (ADJP (RB(...TRUNCATED) | [[[0,0,0],[0,8,8]],[[0,2,2],[0,6,6],[2,5,5],[2,8,8],[3,2,2],[4,2,2],[4,5,5],[4,12,12],[4,15,15],[4,2(...TRUNCATED) | s01e01c09t | "Sheldon, I am so sorry I dragged you through this. It's okay . It wasn't my first pantsing and it w(...TRUNCATED) | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
[{"id":1,"misc":{"parse_tree":"(ROOT (S (S (NP (DT This)) (VP (VBZ is) (NP (NP (CD one)) (PP (IN of)(...TRUNCATED) | [[[0,0,0],[0,4,6],[0,14,14]],[[0,4,4],[2,2,2]],[[0,11,12]],[[0,16,19]],[[1,3,3],[2,5,5],[2,10,10],[2(...TRUNCATED) | s01e01c10t | "This is one of my favorite places to kick back after a quest . They have a great house ale. Wow, co(...TRUNCATED) | tv_the_big_bang_theory | {
"comment": "detokenizer=nltk"
} |
End of preview. Expand in Data Studio
This dataset was generated by reformatting coref-data/mmc_raw into the indiscrim coreference format. See that repo for dataset details.
See ianporada/coref-data for additional conversion details and the conversion script.
Please create an issue in the repo above or in this dataset repo for any questions.
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
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Number of rows:
6,086