Triple

T4423345
Position Surface form Disambiguated ID Type / Status
Subject Nicholas Hytner E95152 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 Hytner, givenName, Nicholas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nicholas
Context triple: [Nicholas Hytner, 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. Rupert
    Rupert is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by various notable figures.
  • C. Rupert
    Rupert is a small town located in Greenbrier County in the state of West Virginia, United States.
  • D. Nicholas Van Orton
    Nicholas Van Orton is a wealthy, emotionally detached investment banker whose life unravels after he becomes entangled in a mysterious and elaborate psychological "game" in the film *The Game*.
  • E. Nicolai
    Nicolai is a German surname historically associated with figures such as the Enlightenment-era publisher and writer Friedrich Nicolai.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3554b36a48190a475ac5474bed132 completed March 13, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f62bbee48190bae8fc7b9cc29086 completed March 14, 2026, 11:58 p.m.
Created at: March 12, 2026, 11:30 p.m.