Triple
T10470362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goya Award for Best Actor |
E246906
|
entity |
| Predicate | hasStatueStyle |
P15314
|
FINISHED |
| Object | bronze bust of Francisco de Goya |
—
|
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: bronze bust of Francisco de Goya | Statement: [Goya Award for Best Actor, hasStatueStyle, bronze bust of Francisco de Goya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatueStyle Context triple: [Goya Award for Best Actor, hasStatueStyle, bronze bust of Francisco de Goya]
-
A.
hasStatue
Indicates that one entity possesses, contains, or is associated with a statue representing or located within it.
-
B.
hasStationStyle
Indicates that one entity (typically a station) possesses or is characterized by a particular architectural or design style.
-
C.
hasStatueNickname
Indicates that an entity (typically a statue) is known or referred to by a particular nickname.
-
D.
hasStatueOrigin
Indicates that a statue was created in, derived from, or originally located in a specified place or source.
-
E.
statuetteShape
chosen
Indicates that one entity has the physical form or outline of a statuette.
- 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_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. |
Created at: April 6, 2026, 12:20 p.m.