Triple
T34457962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilt Chamberlain |
E884552
|
entity |
| Predicate | teamDuring100PointGame |
P38586
|
FINISHED |
| Object | Philadelphia Warriors |
—
|
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: Philadelphia Warriors | Statement: [Wilt Chamberlain, teamDuring100PointGame, Philadelphia Warriors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamDuring100PointGame Context triple: [Wilt Chamberlain, teamDuring100PointGame, Philadelphia Warriors]
-
A.
teamIn100PointGame
chosen
Indicates that a team participated in a game in which at least one team scored 100 or more points.
-
B.
teamDuring73PointGame
Indicates that the entity was the team involved during the referenced 73-point game event.
-
C.
teamFor51PointGame
Indicates the team for which a player was playing when they scored 51 points in a single game.
-
D.
70PointGameTeam
Indicates that a team is associated with a game in which it scored at least 70 points.
-
E.
scored100PointsInAGame
Indicates that an entity achieved a total of 100 points in a single game or match.
- 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.