Triple
T16176876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAFTA Award for Best Costume Design |
E392585
|
entity |
| Predicate | notableLanguageOfCeremony |
P2769
|
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: [BAFTA Award for Best Costume Design, notableLanguageOfCeremony, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLanguageOfCeremony Context triple: [BAFTA Award for Best Costume Design, notableLanguageOfCeremony, English]
-
A.
languageOfCeremony
chosen
Indicates the language in which a ceremony is conducted or officially performed.
-
B.
officialLanguageOfNomination
Indicates the language officially used in the nomination process or documentation for a given entity.
-
C.
notableLanguageOfEligibleFilms
Indicates that there is a notable language associated with the set of films that qualify as eligible under a given criterion or program.
-
D.
isScheduledLanguageOf
Indicates that a particular language is officially planned or designated to be used for a specific event, program, or context.
-
E.
notableMemberLanguage
Indicates that the language is notably associated with or used by a prominent member of the referenced group or 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e22059e7048190b4592cb1516b5f8d |
completed | April 17, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.