Triple

T21270134
Position Surface form Disambiguated ID Type / Status
Subject Bologna–Florence railway E524232 entity
Predicate connectsCity P4245 FINISHED
Object Florence 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: Florence | Statement: [Bologna–Florence railway, connectsCity, Florence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florence
Context triple: [Bologna–Florence railway, connectsCity, Florence]
  • A. Florence chosen
    Florence is a historic Italian city renowned as the cradle of the Renaissance, celebrated for its art, architecture, and cultural influence.
  • B. Florence
    Florence is a small coastal city in western Oregon known for its scenic beaches, sand dunes, and historic Old Town along the Siuslaw River.
  • C. Florence
    Florence is a feminine given name of Latin origin, historically associated with the meaning "prosperous" or "flourishing" and borne by numerous notable figures and places.
  • D. Florence
    Florence is a fictional character in Ali Smith's novel "Spring," playing a pivotal role in the book's exploration of contemporary politics, migration, and human connection.
  • E. Florence
    Florence is a kind, sensible young girl and one of the main human characters in the classic stop-motion children's television series "The Magic Roundabout."
  • 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_69e0b516293c819089458ea2ec85f85e completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73651c9208190a87d45acd6fafaaa completed April 21, 2026, 8:33 a.m.
Created at: April 16, 2026, 4:01 p.m.