Triple
T11848820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thurman Thomas |
E281853
|
entity |
| Predicate | sportNumberOfPlayersPosition |
P92944
|
FINISHED |
| Object | offensive backfield |
—
|
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: offensive backfield | Statement: [Thurman Thomas, sportNumberOfPlayersPosition, offensive backfield]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportNumberOfPlayersPosition Context triple: [Thurman Thomas, sportNumberOfPlayersPosition, offensive backfield]
-
A.
sportNumberOfPlayersOnTeam
Indicates the number of players that make up a single team in a given sport.
-
B.
includesPositionPlayers
chosen
Indicates that a group, team, or lineup contains players assigned to specific positions.
-
C.
sportNumber
Indicates the specific jersey or uniform number associated with an athlete in a sporting context.
-
D.
clubPosition
Indicates the specific role or position an individual holds within a sports club or team.
-
E.
sportNumberOfAppearances
Indicates the total number of times an entity has participated in or appeared in a particular sport or sporting event.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65c72088190b8de9550c455b788 |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.