Triple

T13545455
Position Surface form Disambiguated ID Type / Status
Subject William Merrill E323496 entity
Predicate hasGivenName P17 FINISHED
Object William E772 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: William | Statement: [William Merrill, hasGivenName, William]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William
Context triple: [William Merrill, hasGivenName, William]
  • A. William chosen
    William is a common masculine given name of Germanic origin, widely used in English-speaking countries.
  • B. Thomas
    Thomas is the given name of Thomas Fairfax, 1st Lord Fairfax of Cameron, a prominent Parliamentarian general during the English Civil War.
  • C. Thomas
    Thomas is the given name of Thomas Fairfax, 2nd Lord Fairfax of Cameron, a prominent Parliamentary general during the English Civil War.
  • D. Thomas
    Thomas is the given first name of American actor Tom Sizemore, known for his intense supporting roles in crime and war films.
  • E. Thomas
    Thomas is the formal given name of the American author and journalist Tom Wolfe, known for his pioneering work in New Journalism.
  • 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_69d8076776248190bdf0d4fa1f85a5fc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafdb466881908fb46642dc66849d completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75da2c2008190b43a653a349ea0c7 completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:45 p.m.