Triple

T10584536
Position Surface form Disambiguated ID Type / Status
Subject 77th Academy Awards E249819 entity
Predicate bestActorFilm P5563 FINISHED
Object Ray E231114 NE 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: Ray | Statement: [77th Academy Awards, bestActorFilm, Ray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray
Context triple: [77th Academy Awards, bestActorFilm, Ray]
  • A. Ray
    Ray is a masculine given name commonly used in English-speaking countries, often as a short form of Raymond.
  • B. Ray chosen
    "Ray" is a 2004 biographical film about the life and music of legendary rhythm and blues musician Ray Charles.
  • C. Ray
    Ray is an ancient city near modern-day Tehran in Iran that served as a significant political and cultural center in various Persian empires.
  • D. Ray
    Ray is an open-source distributed computing framework designed to scale Python applications for tasks like machine learning, reinforcement learning, and data processing across clusters.
  • E. Ray
    Ray is a surname of English and Scottish origin borne by various notable individuals across different fields.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d381c9d3d48190a29ee491e1696a0e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d52768da9c8190add1db88bf2e16ea completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b820330819090ed70c6ba29b5c2 completed April 10, 2026, 7:12 p.m.
Created at: April 6, 2026, 12:39 p.m.