Triple
T1976257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crime Laboratory System |
E42919
|
entity |
| Predicate | lawEnforcementRole |
P25776
|
FINISHED |
| Object | support agency |
—
|
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: support agency | Statement: [Crime Laboratory System, lawEnforcementRole, support agency]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawEnforcementRole Context triple: [Crime Laboratory System, lawEnforcementRole, support agency]
-
A.
typeOfLawEnforcement
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
B.
policeCharacter
Indicates that one entity serves as a police officer or law-enforcement figure in relation to another entity.
-
C.
enforcementAgency
chosen
Indicates that one entity serves as the authority responsible for enforcing laws, rules, or regulations related to another entity.
-
D.
lawEnforcementResponse
Indicates the actions or measures taken by law enforcement agencies in reaction to an incident, behavior, or situation.
-
E.
officersAre
Indicates that certain individuals hold the role or position of officers within a specified group, organization, or context.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f9a87c8190816db3888787ad76 |
completed | March 7, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.