Triple

T7170758
Position Surface form Disambiguated ID Type / Status
Subject Alexandre de Lameth E167188 entity
Predicate associatedWith P37 FINISHED
Object Lafayette E87859 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: Lafayette | Statement: [Alexandre de Lameth, associatedWith, Lafayette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lafayette
Context triple: [Alexandre de Lameth, associatedWith, Lafayette]
  • A. Lafayette chosen
    Lafayette was a French aristocrat and military officer who became a key general in the American Revolutionary War and a symbol of Franco-American alliance.
  • B. Lafayette
    Lafayette is a mid-sized city in southern Louisiana known as a cultural hub of Cajun and Creole music, food, and festivals.
  • C. Fort Louis
    Fort Louis is a historic coastal fortification in the Caribbean archipelago of Les Saintes, later renamed Fort Napoléon and now known for its panoramic views and museum.
  • D. Vincennes
    Vincennes is a historic commune just east of Paris, France, known for its medieval Château de Vincennes and long-standing royal connections.
  • E. Lafayette, Louisiana
    Lafayette, Louisiana is a mid-sized city in south-central Louisiana known as the heart of Cajun and Creole culture, with a vibrant music, food, and festival scene.
  • 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_69c68889a2748190a316c5e65360361a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e85ec718819085af59fadee9d22d completed March 27, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b910c2688190b28573c5d58542d5 completed March 28, 2026, 11:18 a.m.
Created at: March 27, 2026, 2:48 p.m.