Triple

T6924090
Position Surface form Disambiguated ID Type / Status
Subject Enschede E160259 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Losser E413748 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: Losser | Statement: [Enschede, hasNeighbouringMunicipality, Losser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Losser
Context triple: [Enschede, hasNeighbouringMunicipality, Losser]
  • A. Losser chosen
    Losser is a municipality in the eastern Netherlands, located in the province of Overijssel near the German border.
  • B. Lorens
    Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
  • C. Lunner
    Lunner is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and role as part of the Hadeland traditional district.
  • D. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • E. Shriever
    Shriever is a surname, a variant spelling of "Shriver," borne by various individuals of English-speaking origin.
  • 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_69c6884d350081908d8a970e4d40ad78 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9fea8d08190b6099a24fbac7de5 completed March 27, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7513bcd2c8190853bc6e8a33a1673 completed March 28, 2026, 3:55 a.m.
Created at: March 27, 2026, 2:26 p.m.