Triple

T7749167
Position Surface form Disambiguated ID Type / Status
Subject Pisa International Airport E175709 entity
Predicate servesCity P82 FINISHED
Object Pisa E32982 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: [Pisa International Airport, servesCity, Pisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pisa
Context triple: [Pisa International Airport, servesCity, Pisa]
  • A. 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.
  • B. Florence
    Florence is the birth name of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics brand.
  • 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 critically acclaimed interactive story and mobile video game that explores the emotional journey of a young woman's first love through minimalist gameplay and visual storytelling.
  • E. Florence
    Florence is a character in John Patrick's play "The Curious Savage," known as one of the eccentric residents of a sanatorium who helps explore themes of sanity, kindness, and societal values.
  • 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_69c69960b3588190a53aa590d31d9544 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703b13af08190b110104fe96ef91e completed March 27, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8fa2a4d388190bbc037a3f89bbf49 completed March 29, 2026, 10:08 a.m.
Created at: March 27, 2026, 4:08 p.m.