Triple

T3314694
Position Surface form Disambiguated ID Type / Status
Subject Wayne Bennett E69653 entity
Predicate givenName P17 FINISHED
Object Wayne E49609 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: Wayne | Statement: [Wayne Bennett, givenName, Wayne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wayne
Context triple: [Wayne Bennett, givenName, Wayne]
  • A. Wayne chosen
    Wayne is a masculine given name of English origin commonly used in the United States and other English-speaking countries.
  • B. Wayne
    Wayne is a suburban community in Pennsylvania’s Main Line region, known for its residential neighborhoods and commuter access to Philadelphia.
  • C. Vaughn
    Vaughn is a surname most prominently associated with English film director and producer Matthew Vaughn, known for stylish action and comic-book adaptations.
  • D. Willis
    Willis is a masculine given name and surname of English origin, often considered a variant or cognate of the name Wilson.
  • E. Conway
    Conway is a surname most notably associated with the influential British mathematician John H. Conway, known for his work in group theory, number theory, and cellular automata such as the Game of Life.
  • 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_69ad85a0bb048190a5458d2738012d61 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb10f97b48190afb9c3864faf8cb2 completed March 8, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3f760348190abd8854c369cb41b completed March 12, 2026, 5:12 p.m.
Created at: March 8, 2026, 3:11 p.m.