Triple

T8094862
Position Surface form Disambiguated ID Type / Status
Subject The Predator E188956 entity
Predicate setting P1957 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: [The Predator, setting, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Georgia
Context triple: [The Predator, setting, 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 character from the musical and film "Burlesque," known for her role as one of the performers in the nightclub where the story unfolds.
  • D. Georgia
    Georgia is a 1995 American drama film starring Jennifer Jason Leigh as a struggling singer overshadowed by her more successful sister.
  • E. Georgia
    "Georgia" is a hit single by American rapper Ludacris, known for its soulful hook and homage to the U.S. state of Georgia.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb429089cc81909e4625f9cc7e305f completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd947cf7a881908b45cf262887da86 completed April 1, 2026, 9:56 p.m.
Created at: March 30, 2026, 5:30 p.m.