Triple
T30997534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conchita |
E789844
|
entity |
| Predicate | nationalContextInFilm |
P72837
|
FINISHED |
| Object | Spanish |
—
|
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 | Statement: [Conchita, nationalContextInFilm, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalContextInFilm Context triple: [Conchita, nationalContextInFilm, Spanish]
-
A.
nationalCinema
Indicates that a film or cinematic work is associated with, produced by, or representative of a particular nation’s cinema.
-
B.
cinematicContext
Indicates the relationship in which something is situated within, shaped by, or relevant to the circumstances, style, or conventions of cinema or film.
-
C.
nationalContextOfWork
chosen
Indicates the country or national setting within which the work or activity is carried out.
-
D.
locatedInNationalContext
Indicates that an entity exists or occurs within the geographical, political, or cultural boundaries of a specific nation.
-
E.
nationalGoverningContext
Indicates the relationship in which an entity operates within, is regulated by, or is relevant to the governance structures, laws, or policies of a specific nation-state.
- 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
Created at: April 29, 2026, 8:56 p.m.