Triple

T566589
Position Surface form Disambiguated ID Type / Status
Subject Academy Award for Best Film Editing E13565 entity
Predicate hasCategoryNumbering P16456 FINISHED
Object one of the original craft categories 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: one of the original craft categories | Statement: [Academy Award for Best Film Editing, hasCategoryNumbering, one of the original craft categories]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCategoryNumbering
Context triple: [Academy Award for Best Film Editing, hasCategoryNumbering, one of the original craft categories]
  • A. hasNumberCategory
    Indicates that an entity is associated with a specific numerical classification or type.
  • B. numberingType
    Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
  • C. hasMajorCategory
    Indicates that something is associated with or classified under a primary, overarching category.
  • D. hasTotalNumber
    Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
  • E. hasCategoryGroup
    Indicates that something is associated with, or belongs to, a broader grouping of related categories.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b01aca48190944408d066519149 completed March 1, 2026, 8:01 p.m.
PD Predicate disambiguation batch_69a494c183b081909304944aa3d0fe8f completed March 1, 2026, 7:34 p.m.
PDg Predicate description generation batch_69a4985952a481908b918350ececf484 completed March 1, 2026, 7:49 p.m.
Created at: March 1, 2026, 7:32 p.m.