Triple

T17189315
Position Surface form Disambiguated ID Type / Status
Subject Plains High School Museum E417186 entity
Predicate locatedIn P40 FINISHED
Object Plains, Georgia E84456 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: Plains, Georgia | Statement: [Plains High School Museum, locatedIn, Plains, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Plains, Georgia
Context triple: [Plains High School Museum, locatedIn, Plains, Georgia]
  • A. Plains, Georgia, United States chosen
    Plains, Georgia, United States, is a small rural town best known as the hometown of former U.S. President Jimmy Carter.
  • B. Plainville, Georgia
    Plainville, Georgia is a small rural city located in northwestern Georgia within Gordon County.
  • C. White Plains, Georgia
    White Plains, Georgia is a small historic town in Greene County known for its rural character and 19th-century roots in east-central Georgia.
  • D. De Soto, Georgia
    De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
  • E. Blakely, Georgia
    Blakely, Georgia is a small city in southwestern Georgia that serves as the administrative and economic center of Early County.
  • 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_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42d986b60819085c515101cfe65fe completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fd0e1448190a9c0eadc7a8a2f6a completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:37 a.m.