Triple
T971775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BAFTA Award for Best Actress in a Leading Role |
E20959
|
entity |
| Predicate | languageOfAwardBody |
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 Actress in a Leading Role, languageOfAwardBody, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfAwardBody Context triple: [BAFTA Award for Best Actress in a Leading Role, languageOfAwardBody, English]
-
A.
awardNameLanguage
Indicates the language in which the name of an award is expressed.
-
B.
officialLanguageOfNomination
Indicates the language officially used in the nomination process or documentation for a given entity.
-
C.
languageOfCeremony
chosen
Indicates the language in which a ceremony is conducted or officially performed.
-
D.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
E.
languageOfEvent
Indicates the language in which an event is conducted, presented, or communicated.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b44c38f08190997e141d424e9e04 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a6aa2c8190aebba71320ab678f |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.