Triple

T7487704
Position Surface form Disambiguated ID Type / Status
Subject Aubagne E176922 entity
Predicate twinnedWith P1072 FINISHED
Object Sabadell E254028 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: Sabadell | Statement: [Aubagne, twinnedWith, Sabadell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabadell
Context triple: [Aubagne, twinnedWith, Sabadell]
  • A. Sabadell chosen
    Sabadell is a major industrial and commercial city in Catalonia, Spain, known historically for its textile industry and now as part of the Barcelona metropolitan area.
  • B. Esplugues de Llobregat
    Esplugues de Llobregat is a municipality in the metropolitan area of Barcelona, Catalonia, known for its residential character and proximity to the Catalan capital.
  • C. Mataró
    Mataró is a coastal city in northeastern Spain known as an important commercial and industrial center on the Mediterranean near Barcelona.
  • D. Sant Feliu de Llobregat
    Sant Feliu de Llobregat is a municipality in the Barcelona metropolitan area of Catalonia, Spain, known as a local administrative center and residential suburb of Barcelona.
  • E. Sant Cugat del Vallès
    Sant Cugat del Vallès is a town near Barcelona in Catalonia, Spain, known for its historic monastery, residential character, and role as an educational and business hub.
  • 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_69c69f24ac508190bb98fe927c0bd065 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f55965ac81909d3c3a5422b22d44 completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c6d7dc08190b5d030e3eff9b108 completed March 28, 2026, 8:39 p.m.
Created at: March 27, 2026, 3:43 p.m.