Triple

T10061476
Position Surface form Disambiguated ID Type / Status
Subject Imola E212999 entity
Predicate locatedBetween P1262 FINISHED
Object Ravenna E26087 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: Ravenna | Statement: [Imola, locatedBetween, Ravenna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ravenna
Context triple: [Imola, locatedBetween, Ravenna]
  • A. Ravenna
    Ravenna is a residential neighborhood in northeast Seattle, Washington, known for its quiet streets, parks, and proximity to the University of Washington.
  • B. Ravenna chosen
    Ravenna is a historic city in northeastern Italy renowned for its well-preserved late Roman and Byzantine mosaics and its role as a former capital of the Western Roman Empire.
  • C. RAVENNA
    RAVENNA is an open, IP-based audio-over-Ethernet networking technology designed for real-time, high-quality audio distribution in broadcast and professional media environments.
  • D. Rimini
    Rimini is a historic Italian coastal city on the Adriatic Sea, renowned for its beaches, Roman and Renaissance landmarks, and vibrant tourism industry.
  • E. Bologna
    Bologna is a historic city in northern Italy renowned for its medieval architecture, rich culinary tradition, and the University of Bologna, one of the oldest universities in the world.
  • 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcfd1fc98819082ec3f2f91151955 completed April 2, 2026, 2:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d8dbe24a64819098bc94a8a62cc46b completed April 10, 2026, 11:15 a.m.
Created at: March 30, 2026, 8:57 p.m.