Triple
T14751773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny Pino as Miguel Galindo |
E346625
|
entity |
| Predicate | seriesMedium |
P115649
|
FINISHED |
| Object | television series |
—
|
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: television series | Statement: [Danny Pino as Miguel Galindo, seriesMedium, television series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesMedium Context triple: [Danny Pino as Miguel Galindo, seriesMedium, television series]
-
A.
filmSerialType
Indicates the type or category of a film serial to which a particular film or episode belongs.
-
B.
animationMedium
Indicates the technique or format used to create or present an animation (e.g., 2D, 3D, stop-motion).
-
C.
seriesFocus
Indicates that one entity serves as the primary subject, theme, or focal point of a series created, presented, or organized by another entity.
-
D.
mediumAdaptation
Indicates that one work has been adapted into another form or medium (e.g., book to film, comic to TV series).
-
E.
homeSeriesGenre
Indicates that a home media series (such as a TV or video series) belongs to or is categorized under a particular genre.
- 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.