Triple

T9400215
Position Surface form Disambiguated ID Type / Status
Subject Nicholas Ray E226448 entity
Predicate givenName P17 FINISHED
Object Nicholas E28979 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: Nicholas | Statement: [Nicholas Ray, givenName, Nicholas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nicholas
Context triple: [Nicholas Ray, givenName, Nicholas]
  • A. Nicholas chosen
    Nicholas is a masculine given name of Greek origin, commonly used in many cultures and historically borne by numerous saints, rulers, and notable figures.
  • B. Nicholas Francis
    Nicholas Francis is a Danish software developer and entrepreneur best known as a co-founder of the game engine and technology company Unity Technologies.
  • C. Nicholas Herrick
    Nicholas Herrick was the father of the 17th-century English lyric poet and cleric Robert Herrick.
  • D. Rupert
    Rupert is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by various notable figures.
  • E. Rupert
    Rupert is a small town located in Greenbrier County in the state of West Virginia, United States.
  • 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_69ca843170f88190800a8ab2b5fc568e completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd5156b9588190bafb6b1c3ee3c0ed completed April 1, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1012753088190bc73b7c577109e76 completed April 4, 2026, 12:16 p.m.
Created at: March 30, 2026, 7:46 p.m.