Triple
T4762668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabaddi |
E105732
|
entity |
| Predicate | firstIncludedInAsianGames |
P59165
|
FINISHED |
| Object | 1990 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 1990 | Statement: [Kabaddi, firstIncludedInAsianGames, 1990]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstIncludedInAsianGames Context triple: [Kabaddi, firstIncludedInAsianGames, 1990]
-
A.
hasNotableFirstAsianWinner
Indicates that an award, competition, or recognition has a first winner of Asian origin who is considered notable or significant.
-
B.
firstAppearedInOlympics
Indicates the event or entity in which something made its debut appearance at the Olympic Games.
-
C.
firstHeldAsCommonwealthGames
Indicates the event or location where something was initially hosted as part of the Commonwealth Games.
-
D.
AsianChampionshipTitles
Indicates the number of championship titles an entity has won in Asian-level competitions or tournaments.
-
E.
olympicDebut
Indicates the event or year in which an entity first participated in the Olympic Games.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd686ef1b08190ad60375592c9d6c0 |
completed | March 20, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69bd622807f881908e4bcb14f7731bac |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd686dc7b88190b41e8a362701080d |
completed | March 20, 2026, 3:31 p.m. |
Created at: March 20, 2026, 1:20 p.m.