Triple

T8996365
Position Surface form Disambiguated ID Type / Status
Subject Offenbach am Main E214922 entity
Predicate hasTwinTown P919 FINISHED
Object Mataró E254926 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: Mataró | Statement: [Offenbach am Main, hasTwinTown, Mataró]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mataró
Context triple: [Offenbach am Main, hasTwinTown, Mataró]
  • A. Mataró chosen
    Mataró is a coastal city in northeastern Spain known as an important commercial and industrial center on the Mediterranean near Barcelona.
  • B. Sabadell
    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.
  • C. 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.
  • D. Lleida
    Lleida is a historic city in western Catalonia, Spain, known for its medieval Seu Vella cathedral and role as a regional agricultural and commercial center.
  • E. 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.
  • 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_69ca83a05c608190bdfdbdb25e994b39 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc68df33c48190a5017426e59c0bc4 completed April 1, 2026, 12:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffd9bd544819083adf00db6a4a473 completed April 3, 2026, 5:49 p.m.
Created at: March 30, 2026, 7:04 p.m.