Triple
T34457963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilt Chamberlain |
E884552
|
entity |
| Predicate | opponentDuring100PointGame |
P38587
|
FINISHED |
| Object | New York Knicks |
—
|
NE NERFINISHED |
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: New York Knicks | Statement: [Wilt Chamberlain, opponentDuring100PointGame, New York Knicks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opponentDuring100PointGame Context triple: [Wilt Chamberlain, opponentDuring100PointGame, New York Knicks]
-
A.
opponentIn100PointGame
chosen
Indicates that two entities are opponents facing each other in a game or match that is played to 100 points.
-
B.
dateOf100PointGame
Indicates the date on which a specific 100-point game occurred.
-
C.
scored100PointsInAGame
Indicates that an entity achieved a total of 100 points in a single game or match.
-
D.
opponentFinalScore
Indicates the final score achieved by an opposing participant or team in a contest or game.
-
E.
opponentInComeback
Indicates that an entity serves as the opposing side or competitor in a situation characterized as a comeback (e.g., recovering from a disadvantage).
- F. None of above.
Provenance (3 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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7197872e881909823c01d2a819998 |
completed | May 3, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f71824431081908d9685d2462ea242 |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 2 a.m.