Triple
T23896698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clayne Crawford as Martin Riggs |
E600921
|
entity |
| Predicate | copType |
P153978
|
FINISHED |
| Object | detectiveWithRecklessMethods |
—
|
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: detectiveWithRecklessMethods | Statement: [Clayne Crawford as Martin Riggs, copType, detectiveWithRecklessMethods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: copType Context triple: [Clayne Crawford as Martin Riggs, copType, detectiveWithRecklessMethods]
-
A.
coachType
Indicates the specific category or role of a coach associated with an entity (e.g., head coach, assistant coach, position coach).
-
B.
craftType
Indicates the specific kind or category of craft or vessel associated with an entity.
-
C.
patrolType
Indicates the specific kind or category of patrol activity being carried out or assigned.
-
D.
coneType
Indicates the specific category or style of cone associated with an entity (e.g., type, shape, or design of the cone).
-
E.
ipoType
Indicates the type or category of an entity’s initial public offering (IPO) event.
- 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_69e295341ac0819080647f2908af793c |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cdda39448190bdefa953e0558583 |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 8:25 p.m.