Triple

T12623551
Position Surface form Disambiguated ID Type / Status
Subject BAFTA film craft awards E301450 entity
Predicate alsoRecognizes P4733 FINISHED
Object technical disciplines in filmmaking 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: technical disciplines in filmmaking | Statement: [BAFTA film craft awards, alsoRecognizes, technical disciplines in filmmaking]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: alsoRecognizes
Context triple: [BAFTA film craft awards, alsoRecognizes, technical disciplines in filmmaking]
  • A. areRecognizedBy
    Indicates that one entity acknowledges, identifies, or accepts another entity as valid, known, or legitimate.
  • B. recognizedAs
    Indicates that one entity is acknowledged or accepted as having the identity, role, status, or classification of another entity.
  • C. recognizedFor
    Indicates that one entity is acknowledged, credited, or honored for a particular achievement, quality, contribution, or work associated with another entity.
  • D. canRecognize
    Indicates that one entity has the ability to identify or distinguish another entity based on its features or characteristics.
  • E. recognizedIn chosen
    Indicates that an entity is formally acknowledged, honored, or given recognition within a particular context, setting, or domain.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9617b07ec8190b714f04ae6654060 completed April 10, 2026, 8:45 p.m.
PD Predicate disambiguation batch_69d960b195108190ac25bd95e644ace4 completed April 10, 2026, 8:42 p.m.
Created at: April 9, 2026, 5:14 p.m.