Triple
T37320123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Picture for Munich |
E926451
|
entity |
| Predicate | nominatedFilmCountryOfOrigin |
P188856
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Academy Award for Best Picture for Munich, nominatedFilmCountryOfOrigin, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nominatedFilmCountryOfOrigin Context triple: [Academy Award for Best Picture for Munich, nominatedFilmCountryOfOrigin, United States]
-
A.
nominatedPersonNationality
Indicates that the specified nationality is the country or national identity of the person who has been nominated.
-
B.
nominatedIn
Indicates that an entity has been formally put forward as a candidate for an award, position, or recognition within a specific event, context, or time period.
-
C.
bestPictureWinnerCountry
Indicates the country associated with the film that won the Best Picture award in a given year or context.
-
D.
bestForeignFilmHonoraryAwardCountry
Indicates the country that received an honorary award for best foreign film.
-
E.
academyAwardBestForeignLanguageFilmNomination
Indicates that a film received a nomination for the Academy Award for Best Foreign Language Film.
- 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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbad1b3ba08190ad69e21461333f2e |
completed | May 6, 2026, 9:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.