Triple
T37320131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Picture for Munich |
E926451
|
entity |
| Predicate | languageOfNominatedFilm |
P93753
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Academy Award for Best Picture for Munich, languageOfNominatedFilm, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfNominatedFilm Context triple: [Academy Award for Best Picture for Munich, languageOfNominatedFilm, English]
-
A.
honouredFilmLanguage
Indicates that a particular language is the one in which a film was created or presented that received an honor, award, or special recognition.
-
B.
basedInFilmLanguage
Indicates that something is created, presented, or expressed using the language employed in a particular film.
-
C.
primaryFilmingLanguage
chosen
Indicates the main language in which a film or audiovisual work was originally filmed or recorded.
-
D.
filmedInLanguage
Indicates that a film or video work was originally recorded using a particular spoken or signed language.
-
E.
officialLanguageOfNomination
Indicates the language officially used in the nomination process or documentation for a given entity.
- 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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a01839b071481909f9cc79a6a09387d |
completed | May 11, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_6a017edbed688190baa61cbae5110c8e |
completed | May 11, 2026, 7:01 a.m. |
Created at: May 3, 2026, 4:16 p.m.