Triple

T6646126
Position Surface form Disambiguated ID Type / Status
Subject Aphrodisia E150704 entity
Predicate majorCultCenter P9995 FINISHED
Object Corinth E61494 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: Corinth | Statement: [Aphrodisia, majorCultCenter, Corinth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Corinth
Context triple: [Aphrodisia, majorCultCenter, Corinth]
  • A. Corinth
    Corinth is a small unincorporated community located in Coweta County, Georgia, United States.
  • B. Corinth chosen
    Corinth was an influential ancient Greek city-state strategically located on the Isthmus of Corinth, known for its wealth, maritime trade, and cultural significance.
  • C. Corinth
    Corinth is a small town and village in Saratoga County, New York, known for its historic paper mills and location along the Hudson River near the Adirondack foothills.
  • D. Corinto
    Corinto is a major Pacific seaport town in northwestern Nicaragua that serves as one of the country’s principal maritime gateways for trade.
  • E. Sikyon
    Sikyon was an ancient Greek city-state in the northern Peloponnese, known for its artistic and cultural achievements, especially in sculpture and painting.
  • 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_69c687f1a3048190828b7342f7125d5c completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b01cecc48190a6d2c26d8d5ab80c completed March 27, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eef48b488190ac08dc37d4a5d514 completed March 27, 2026, 8:56 p.m.
Created at: March 27, 2026, 2 p.m.