Triple
T10470355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goya Award for Best Actor |
E246906
|
entity |
| Predicate | hasAwardedForFilmIndustry |
P94202
|
FINISHED |
| Object | Spanish film industry |
—
|
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: Spanish film industry | Statement: [Goya Award for Best Actor, hasAwardedForFilmIndustry, Spanish film industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAwardedForFilmIndustry Context triple: [Goya Award for Best Actor, hasAwardedForFilmIndustry, Spanish film industry]
-
A.
associatedAwardWinningFilm
Indicates that there is a relationship between an entity and a film with which it is connected, where that film has received an award.
-
B.
mostAwardsFilm
Indicates that a film is the one that has received the highest number of awards within a given set or context.
-
C.
awardedForTheater
Indicates that an award or honor is given in recognition of achievements or contributions in the field of theater.
-
D.
hasAudienceAward
Indicates that an entity has received an award determined by audience or public voting.
-
E.
firstAwardedForFilm
Indicates the film for which an entity (such as a person or award) was first given or received an award.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509305fec81908b1acd91ae1f875d |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d4fe058fcc81909428137d9ffd6d90 |
completed | April 7, 2026, 12:52 p.m. |
Created at: April 6, 2026, 12:20 p.m.