Triple
T29085544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Survivor: Game Changers |
E734101
|
entity |
| Predicate | winnerOccupationAtTime |
P107055
|
FINISHED |
| Object | police officer |
—
|
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: police officer | Statement: [Survivor: Game Changers, winnerOccupationAtTime, police officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerOccupationAtTime Context triple: [Survivor: Game Changers, winnerOccupationAtTime, police officer]
-
A.
laterOccupationApproxDate
Indicates an approximate date or time period when a subject began a subsequent occupation or role after an earlier one.
-
B.
historicalHolderOccupation
Indicates that an entity historically held a particular occupation or professional role.
-
C.
winnerProfession
chosen
Indicates that the associated profession is the occupation or field of work of the winner in a given event or competition.
-
D.
eraOfOccupation
Indicates the time period during which an occupation or role was held or practiced.
-
E.
winnerLaterOccupation
Indicates that the person who won a particular event later held a specified occupation.
- 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_69f05b0c0f28819086eae6e84f2ae472 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: April 28, 2026, 11 a.m.