Triple

T21034873
Position Surface form Disambiguated ID Type / Status
Subject Cimabue E518162 entity
Predicate placeOfDeath P21 FINISHED
Object Pisa NE NERFINISHED

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: [Cimabue, placeOfDeath, Pisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pisa
Context triple: [Cimabue, placeOfDeath, Pisa]
  • A. Pisa
    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.
  • B. Pisa chosen
    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.
  • 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 neighborhood in South Los Angeles known for its dense urban character, diverse working-class community, and proximity to major transportation corridors.
  • E. Florence
    Florence is a small town in Fremont County, Colorado, known for its historic downtown and role as a gateway to nearby outdoor attractions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b503275c8190afd9a163f997c709 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc858d808190a8489aac801a4f51 completed April 21, 2026, 4:26 a.m.
Created at: April 16, 2026, 2:01 p.m.