Triple

T6451230
Position Surface form Disambiguated ID Type / Status
Subject Christopher A. Wray E139869 entity
Predicate barAdmission P3471 FINISHED
Object Georgia E14900 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: Georgia | Statement: [Christopher A. Wray, barAdmission, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georgia
Context triple: [Christopher A. Wray, barAdmission, Georgia]
  • A. Georgia chosen
    Georgia is a southeastern U.S. state known for its diverse landscapes, historic cities like Atlanta and Savannah, and significant roles in both the Civil War and the civil rights movement.
  • B. Georgia
    Georgia is a country at the crossroads of Eastern Europe and Western Asia, known for its ancient culture, mountainous landscapes, and historic role along the Silk Road.
  • C. Georgia
    "Georgia" is a hit single by American rapper Ludacris, known for its soulful hook and homage to the U.S. state of Georgia.
  • D. Georgia
    Georgia is a character from the musical and film "Burlesque," known for her role as one of the performers in the nightclub where the story unfolds.
  • E. Georgia
    Georgia is a 1995 American drama film starring Jennifer Jason Leigh as a struggling singer overshadowed by her more successful sister.
  • 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_69c008b301948190a35854e5284dc822 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c069b4171c8190b0acad78700998ed completed March 22, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65385f80081908e989b17529808c5 completed March 27, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:47 p.m.