Triple
T33873481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La pregunta de sus ojos |
E868286
|
entity |
| Predicate | filmAdaptationAward |
P178120
|
FINISHED |
| Object | Academy Award for Best Foreign Language Film |
—
|
NE NERFINISHED |
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: Academy Award for Best Foreign Language Film | Statement: [La pregunta de sus ojos, filmAdaptationAward, Academy Award for Best Foreign Language Film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmAdaptationAward Context triple: [La pregunta de sus ojos, filmAdaptationAward, Academy Award for Best Foreign Language Film]
-
A.
filmAdaptationOfWork
Indicates that a film is an adaptation based on the narrative content of a specific original work.
-
B.
inFilmAdaptation
Indicates that one work or element appears within, or is incorporated into, a film adaptation of another work.
-
C.
filmAdaptationStarred
Indicates that a particular person played a starring role in a specific film adaptation of a work.
-
D.
filmAdaptationMusicBy
Indicates that the music for a film adaptation was composed or created by the specified person or entity.
-
E.
filmAdaptationGenre
Indicates that a film adaptation 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_69f34995029081909ede0f7df73d1a5e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70c53062c8190b4cb7be22ab00bc7 |
completed | May 3, 2026, 8:50 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70b94784c8190970d654e066eb50d |
completed | May 3, 2026, 8:47 a.m. |
Created at: May 1, 2026, 1:47 a.m.