Triple

T10495073
Position Surface form Disambiguated ID Type / Status
Subject Nuts in May E247515 entity
Predicate mainCharacter P1183 FINISHED
Object Ray E19092 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: [Nuts in May, mainCharacter, Ray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray
Context triple: [Nuts in May, mainCharacter, Ray]
  • A. Ray chosen
    Ray is a masculine given name commonly used in English-speaking countries, often as a short form of Raymond.
  • B. Ray
    "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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5098be488819083d614f528cd82fb completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dcbafe9481908fb23cfdf150adac completed April 10, 2026, 11:19 a.m.
Created at: April 6, 2026, 12:24 p.m.