Triple

T7637464
Position Surface form Disambiguated ID Type / Status
Subject West Point, Mississippi E172914 entity
Predicate namedAfter P63 FINISHED
Object West Point, Georgia E32086 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: West Point, Georgia | Statement: [West Point, Mississippi, namedAfter, West Point, Georgia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: West Point, Georgia
Context triple: [West Point, Mississippi, namedAfter, West Point, Georgia]
  • A. West Point, Georgia chosen
    West Point, Georgia is a small city in western Georgia along the Chattahoochee River, known historically as a textile mill town and now for hosting a major Kia Motors manufacturing plant.
  • B. Union Point, Georgia
    Union Point, Georgia is a small historic city in Greene County known for its railroad heritage and preserved 19th-century architecture.
  • C. Vidette, Georgia
    Vidette, Georgia is a small unincorporated rural community located in Burke County in the eastern part of the state.
  • D. Du Pont, Georgia
    Du Pont, Georgia is a small rural town in southern Georgia, United States, known for its historic ties to the region’s timber and railroad industries.
  • E. De Soto, Georgia
    De Soto, Georgia is a small rural city located in southwestern Georgia in the United States.
  • 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_69c69952849881908fdcea7a93bfc307 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fac953e08190a2f50bf783c49faf completed March 27, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a2159cd0819085bfdb8c7694077b completed March 29, 2026, 3:52 a.m.
Created at: March 27, 2026, 3:57 p.m.