Triple

T17844999
Position Surface form Disambiguated ID Type / Status
Subject Netanya E445634 entity
Predicate hasTwinTown P919 FINISHED
Object Bournemouth 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: Bournemouth | Statement: [Netanya, hasTwinTown, Bournemouth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bournemouth
Context triple: [Netanya, hasTwinTown, Bournemouth]
  • A. Bournemouth chosen
    Bournemouth is a large coastal resort town on England’s south coast, known for its sandy beaches, tourism, and role as a regional commercial and transport hub.
  • B. Poole
    Poole is a coastal town and seaport in Dorset, England, known for its large natural harbour and maritime activities.
  • C. Bristol
    Bristol is a historic port city in southwest England known for its maritime heritage, vibrant cultural scene, and distinctive Georgian and Victorian architecture.
  • D. Bristol
    Bristol is a city in central Connecticut known for being the home of ESPN and for its historic clock-making industry.
  • E. Bristol
    Bristol is a city in central Connecticut known historically for its clock-making industry and as the longtime home of ESPN’s headquarters.
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48ff980048190b496c55b83b3b318 completed April 19, 2026, 8:19 a.m.
Created at: April 10, 2026, 10:16 a.m.