Triple
T20283477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buddy Manucci |
E503212
|
entity |
| Predicate | lawEnforcementUnitType |
P7908
|
FINISHED |
| Object | undercover unit |
—
|
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: undercover unit | Statement: [Buddy Manucci, lawEnforcementUnitType, undercover unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawEnforcementUnitType Context triple: [Buddy Manucci, lawEnforcementUnitType, undercover unit]
-
A.
policeUnit
Indicates that one entity is a police unit (such as a department, squad, or division) associated with or responsible for another entity.
-
B.
policeDepartmentType
Indicates the specific organizational category or classification of a police department (e.g., municipal, state, federal).
-
C.
typeOfLawEnforcement
chosen
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
D.
enforcementAgency
Indicates that one entity serves as the authority responsible for enforcing laws, rules, or regulations related to another entity.
-
E.
lawEnforcementLabel
Indicates that an entity has been designated, tagged, or classified by a law enforcement authority for monitoring, identification, or investigative purposes.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6769049b48190bc449557b79b9e81 |
completed | April 20, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 10:48 a.m.