Triple

T11558594
Position Surface form Disambiguated ID Type / Status
Subject Oenomaus E274075 entity
Predicate residence P75 FINISHED
Object Pisa E935707 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: Pisa | Statement: [Oenomaus, residence, Pisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pisa
Context triple: [Oenomaus, residence, Pisa]
  • A. Pisa
    Pisa is a historic Italian city in Tuscany best known for its iconic Leaning Tower and as a significant center of medieval trade, learning, and architecture.
  • B. Pisa chosen
    Pisa is an ancient city in the Peloponnese region of Greece, historically significant as a center near Olympia and associated with early Greek myth and athletics.
  • C. Florence
    Florence is a city in northwestern Alabama known as part of the Muscle Shoals metropolitan area and for its rich musical and cultural heritage.
  • D. Florence
    Florence is a central character in James Baldwin's novel "Go Tell It on the Mountain," known as John Grimes's strong-willed, embittered aunt whose life story reveals the burdens of race, gender, and family in early 20th-century America.
  • E. Florence
    Florence is a neighborhood in South Los Angeles known for its dense urban character, diverse working-class community, and proximity to major transportation corridors.
  • 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88a888e8481909386009b9603e4d3 completed April 10, 2026, 5:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee86b56e4081908746bb3355f6ec47 completed April 26, 2026, 9:42 p.m.
Created at: April 8, 2026, 9:37 p.m.