Triple
T18913287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergeant Gavin Troy |
E462657
|
entity |
| Predicate | policeRankInStory |
P47215
|
FINISHED |
| Object | Detective Sergeant |
—
|
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: Detective Sergeant | Statement: [Sergeant Gavin Troy, policeRankInStory, Detective Sergeant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policeRankInStory Context triple: [Sergeant Gavin Troy, policeRankInStory, Detective Sergeant]
-
A.
policeRank
chosen
Indicates that one entity holds a specific rank or position within a police organization relative to another entity.
-
B.
policeRankStructure
Indicates the hierarchical ranking relationship that defines levels of authority and command within a police organization.
-
C.
policeCharacter
Indicates that one entity serves as a police officer or law-enforcement figure in relation to another entity.
-
D.
lawEnforcementInStory
Indicates that law enforcement personnel or activities are present, involved, or play a role within the narrative of the story.
-
E.
civilServiceRank
Indicates that one entity holds a specific rank or position within a civil service hierarchy relative to another entity or classification.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c624516c81909e6bf04707d3c71c |
completed | April 20, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:58 a.m.