Triple
T14751783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Pino as Miguel Galindo |
E346625
|
entity |
| Predicate | characterIndustry |
P115650
|
FINISHED |
| Object | drug trafficking |
—
|
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: drug trafficking | Statement: [Danny Pino as Miguel Galindo, characterIndustry, drug trafficking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterIndustry Context triple: [Danny Pino as Miguel Galindo, characterIndustry, drug trafficking]
-
A.
occupationInFilm
Indicates that an entity has a specific occupation or role within the context of a particular film.
-
B.
genreOfWorkCharacterIsIn
Indicates the specific genre of the creative work in which a given character appears.
-
C.
notableIndustry
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
-
D.
musicIndustryRole
Indicates the professional function or position an entity holds within the music industry ecosystem.
-
E.
genreOfWorkActedIn
Indicates that an entity is the genre category of a work in which another entity performed or acted.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d40efc8190bb1be34c19a2b57c |
completed | April 14, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:30 a.m.