Triple

T19736467
Position Surface form Disambiguated ID Type / Status
Subject Moss Station E473995 entity
Predicate near P350 FINISHED
Object Moss town centre 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: Moss town centre | Statement: [Moss Station, near, Moss town centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moss town centre
Context triple: [Moss Station, near, Moss town centre]
  • A. Moss town center
    Moss town center is the main commercial and administrative hub of the coastal city of Moss in southeastern Norway.
  • B. Moss city centre chosen
    Moss city centre is the main commercial and administrative hub of the coastal town of Moss in southeastern Norway.
  • C. Moss Park
    Moss Park is a downtown Toronto neighbourhood known for its large public housing complexes, community services, and proximity to the city’s core.
  • D. Mosswood Park
    Mosswood Park is a historic public park in Oakland, California, known for its recreation facilities, open green spaces, and community events.
  • E. Moss city hall
    Moss city hall is the main administrative and political center of the city of Moss in Norway, housing the offices and chambers of the local government.
  • 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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6515ddea881909ea831b7bc16d934 completed April 20, 2026, 4:16 p.m.
Created at: April 10, 2026, 1:47 p.m.