Triple
T34739742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Jason Witten |
E1001461
|
entity |
| Predicate | playedSeasonCountWithTeam |
P14050
|
FINISHED |
| Object | Dallas Cowboys: 16 seasons |
—
|
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: Dallas Cowboys: 16 seasons | Statement: [Christopher Jason Witten, playedSeasonCountWithTeam, Dallas Cowboys: 16 seasons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedSeasonCountWithTeam Context triple: [Christopher Jason Witten, playedSeasonCountWithTeam, Dallas Cowboys: 16 seasons]
-
A.
numberOfSeasonsWithTeam
chosen
Indicates the total count of seasons an entity (e.g., a player or coach) has spent with a particular team.
-
B.
playedCareerGamesForTeam
Indicates that an athlete has played official career games as a member of the specified team.
-
C.
sportNumberOfSeasonsInLeague
Indicates the total count of seasons an entity has participated in a particular sports league.
-
D.
teamSeasonParticipated
Indicates that a team took part in a particular sports season.
-
E.
playedEntireCareerForSingleFranchise
Indicates that an athlete spent their entire professional career playing for only one franchise or team.
- 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_69f76daf739881909ed3554f98a2b433 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: May 3, 2026, 3:59 p.m.