Triple
T14751778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Pino as Miguel Galindo |
E346625
|
entity |
| Predicate | characterRoleType |
P16411
|
FINISHED |
| Object | antagonist |
—
|
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: antagonist | Statement: [Danny Pino as Miguel Galindo, characterRoleType, antagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleType Context triple: [Danny Pino as Miguel Galindo, characterRoleType, antagonist]
-
A.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to another entity.
-
B.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
C.
typeOfRole
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
D.
actingRoleType
chosen
Indicates the specific type or category of role an entity performs when acting in a particular capacity or function.
-
E.
themeRole
Indicates that an entity is the primary participant undergoing or affected by the action or event expressed by a predicate.
- 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_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. |
Created at: April 10, 2026, 1:30 a.m.