Triple

T4391933
Position Surface form Disambiguated ID Type / Status
Subject Nicky Campbell E99383 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: [Nicky Campbell, givenName, Nicholas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nicholas
Context triple: [Nicky Campbell, 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_69b345506b408190b0e3dee616738a7d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35285592881909fcdea225a655950 completed March 12, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e530428881908d125971263bd747 completed March 14, 2026, 10:46 p.m.
Created at: March 12, 2026, 11:19 p.m.