Triple
T3875992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Craig Biggio |
E92500
|
entity |
| Predicate | playedEntireCareerForOneFranchise |
P14860
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Craig Biggio, playedEntireCareerForOneFranchise, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedEntireCareerForOneFranchise Context triple: [Craig Biggio, playedEntireCareerForOneFranchise, true]
-
A.
playedEntireCareerForSingleFranchise
chosen
Indicates that an athlete spent their entire professional career playing for only one franchise or team.
-
B.
spentEntireMLBCareerWith
Indicates that a player spent their entire Major League Baseball career with a single team.
-
C.
leagueParticipatedInAsPlayer
Indicates that a person, in the role of a player, took part in competitions organized by a specific league.
-
D.
careerSpanTeam
Indicates the team for which an individual’s entire career span (or a defined portion of it) is being measured or associated.
-
E.
winnerCareerSpanTeam
Indicates the team for which a winner competed during the span of their professional career.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.