Triple
T16847923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Paso Sun Kings |
E409592
|
entity |
| Predicate | notablePlayerOccupation |
P125090
|
FINISHED |
| Object | actor |
—
|
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: actor | Statement: [El Paso Sun Kings, notablePlayerOccupation, actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notablePlayerOccupation Context triple: [El Paso Sun Kings, notablePlayerOccupation, actor]
-
A.
notableAthlete
Indicates that the subject is a well-known or distinguished athlete associated with the object (such as a sport, team, or organization).
-
B.
notableCharacterOccupation
Indicates that a notable character is associated with a specific occupation or professional role.
-
C.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
D.
notableHolderOccupation
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
-
E.
notableAthleteFrom
Indicates that an athlete is notably associated with or originates from a particular place or region.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b376bac48190ae09f29a28c55f8c |
completed | April 18, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:24 a.m.