Triple
T10072282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Vincennes |
E213657
|
entity |
| Predicate | notableSceneContext |
P7326
|
FINISHED |
| Object | investigation of a high-profile murder case |
—
|
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: investigation of a high-profile murder case | Statement: [Jack Vincennes, notableSceneContext, investigation of a high-profile murder case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSceneContext Context triple: [Jack Vincennes, notableSceneContext, investigation of a high-profile murder case]
-
A.
notableScene
chosen
Indicates that a particular scene is especially significant, memorable, or noteworthy within a work or context.
-
B.
notableStage
Indicates that an entity is recognized as an important or distinguished stage or phase in relation to another entity or process.
-
C.
notableCapture
Indicates that one entity captured or seized another in a way considered historically or contextually significant.
-
D.
notableDuring
Indicates that something was especially prominent, active, or significant during a particular time period or event.
-
E.
partOfScene
Indicates that one entity functions as a component or element within a larger scene or setting involving another entity.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd013c9d0819091ebe6fc399832de |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:59 p.m.