Triple

T9257588
Position Surface form Disambiguated ID Type / Status
Subject Frank James E222484 entity
Predicate givenName P17 FINISHED
Object Franklin E2850 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: Franklin | Statement: [Frank James, givenName, Franklin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franklin
Context triple: [Frank James, givenName, Franklin]
  • A. Franklin chosen
    Franklin is the given name of Franklin D. Roosevelt, the 32nd president of the United States who led the country through the Great Depression and World War II.
  • B. 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.
  • C. Franklin
    Franklin McCain was an American civil rights activist best known as one of the Greensboro Four who led the 1960 Woolworth’s lunch counter sit-in in North Carolina.
  • D. Franklin
    Franklin is an independent city in southeastern Virginia known for its small-town character and historical ties to the regional lumber and paper industries.
  • E. Franklin
    Franklin is the given first name of former American soccer player Frankie Hejduk, a longtime defender for the U.S. national team and Major League Soccer.
  • 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_69ca841e4cd481908e738c74e958eaea completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd06b660448190b6bc04beff0f5512 completed April 1, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09be75fd88190b6e99b0884dcc14c completed April 4, 2026, 5:04 a.m.
Created at: March 30, 2026, 7:32 p.m.