Triple
T34272849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cornelius Bennett |
E879366
|
entity |
| Predicate | nflPositionCategory |
P178731
|
FINISHED |
| Object | linebacker |
—
|
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: linebacker | Statement: [Cornelius Bennett, nflPositionCategory, linebacker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nflPositionCategory Context triple: [Cornelius Bennett, nflPositionCategory, linebacker]
-
A.
HeismanTrophyPosition
Indicates the playing position associated with a recipient of the Heisman Trophy.
-
B.
roleAtTampaBayBuccaneers
Indicates that an entity holds or held a specific role or position within the Tampa Bay Buccaneers organization.
-
C.
roleAtSanFrancisco49ers
Indicates that an entity holds or has held a specific role or position with the San Francisco 49ers organization.
-
D.
nflId
Indicates a unique identifier assigned to an NFL player or entity within the dataset, used to distinguish it from all others.
-
E.
coachPositionPlayed
Indicates the role or position a coach played (typically as a player) in the sport they are associated with.
- 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_69f349b4f5fc819094b441d18e95e5f1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f713bfdc148190a249a7874320bab8 |
completed | May 3, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f7135fa2988190a20a94cfe616d754 |
completed | May 3, 2026, 9:20 a.m. |
Created at: May 1, 2026, 1:56 a.m.