Triple

T19753199
Position Surface form Disambiguated ID Type / Status
Subject Story Musgrave E474434 entity
Predicate givenName P17 FINISHED
Object Franklin NE NERFINISHED

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: Franklin | Statement: [Story Musgrave, givenName, Franklin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franklin
Context triple: [Story Musgrave, givenName, Franklin]
  • A. Franklin
    Franklin is the middle name of American inventor and engineer Charles F. Kettering, known for his influential work in automotive and industrial innovation.
  • B. Franklin chosen
    Franklin is the given first name of F. Story Musgrave, the American physician and NASA astronaut known for his work on multiple Space Shuttle missions.
  • C. Franklin
    Franklin is a wealthy, hospitable landowner and one of the storytellers in Geoffrey Chaucer’s The Canterbury Tales, known for his focus on gentility and marital harmony.
  • D. Franklin
    Franklin is a thoughtful and good-natured friend of Charlie Brown in the Peanuts comic strip, notable as one of the first Black characters in mainstream American comics.
  • E. Franklin
    Franklin is a small city in central Indiana known for its historic downtown, Franklin College, and role as a suburban community within the greater Indianapolis region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51940a0819087bd2996f98da668 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6529cae048190b4f8e6ba409bcf8e completed April 20, 2026, 4:21 p.m.
Created at: April 10, 2026, 1:48 p.m.