Triple
T194654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Belichick |
E3792
|
entity |
| Predicate | positionPlayedInCollege |
P7105
|
FINISHED |
| Object | center |
—
|
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: center | Statement: [Bill Belichick, positionPlayedInCollege, center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionPlayedInCollege Context triple: [Bill Belichick, positionPlayedInCollege, center]
-
A.
leaguePlayedIn
Indicates that a sports team or player has participated in competitions within a particular league.
-
B.
collegeTeam
Indicates that one entity is a sports team that represents or is affiliated with a particular college or university.
-
C.
NCAATournamentAppearance
Indicates that an entity has participated in at least one NCAA basketball tournament.
-
D.
playedFor
Indicates that one entity has been a member of or participated as a player for a particular team, organization, or group.
-
E.
isLargestCollegeAt
Indicates that one college is the largest (typically by enrollment, size, or capacity) among all colleges at a particular institution or location.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25969425081908e178db8ba4631c2 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a256769ad8819083c1d83082c0215e |
completed | Feb. 28, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69a2582b7f648190b0ef676b8bdc1c65 |
completed | Feb. 28, 2026, 2:51 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.