Triple
T30837983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony Muñoz |
E785415
|
entity |
| Predicate | numberRetiredByTeam |
P77341
|
FINISHED |
| Object | Cincinnati Bengals |
—
|
NE NERFINISHED |
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: Cincinnati Bengals | Statement: [Anthony Muñoz, numberRetiredByTeam, Cincinnati Bengals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberRetiredByTeam Context triple: [Anthony Muñoz, numberRetiredByTeam, Cincinnati Bengals]
-
A.
nbaTeamNumberRetiredBy
Indicates that a specific jersey number has been officially retired by a particular NBA team in honor of a player or significant contribution.
-
B.
hasRetiredPlayersFrom
Indicates that an entity has players who previously played for it and have since retired, originating from the specified source entity (e.g., team, league, or country).
-
C.
leagueRetiredNumberBy
Indicates that a sports league has officially retired a specific jersey number in honor of a particular person or entity.
-
D.
nationalTeamRetirementYear
Indicates the year in which an individual ended their participation in a national team.
-
E.
retiredJerseyNumberByTeam
chosen
Indicates that a sports team has officially retired a specific jersey number in honor of a player or figure, making it unavailable for future use by team members.
- 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_69f224b73d8c81908129383bfb397c87 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00a2f0d1588190a936ea7df0ef0464 |
completed | May 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_6a00a28ccd94819085b5e123f5a4769e |
completed | May 10, 2026, 3:21 p.m. |
Created at: April 29, 2026, 8:45 p.m.