Triple

T12132367
Position Surface form Disambiguated ID Type / Status
Subject Stockel – Stokkel E288963 entity
Predicate hasLanguageVariantName P15 FINISHED
Object Stokkel E963972 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: Stokkel | Statement: [Stockel – Stokkel, hasLanguageVariantName, Stokkel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stokkel
Context triple: [Stockel – Stokkel, hasLanguageVariantName, Stokkel]
  • A. Stockel – Stokkel
    Stockel – Stokkel is a metro station in the eastern part of Brussels serving as the terminus of line 1.
  • B. Stockel chosen
    Stockel is a residential neighborhood and metro terminus in the Woluwe-Saint-Pierre municipality of Brussels, Belgium.
  • C. Stod
    Stod is a small town in the Plzeň Region of the Czech Republic that serves as a local administrative and service center for surrounding municipalities.
  • D. Stabekk
    Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
  • E. Kestel
    Kestel is a town and district in northwestern Turkey, situated near the city of Bursa in Bursa Province.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158b34648190b5eecdf9b07fbb3f completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a79dd148190835c2679fb2df3b1 completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:49 p.m.