Triple

T10838559
Position Surface form Disambiguated ID Type / Status
Subject Hoogkerk E255825 entity
Predicate hasNeighbouringSettlement P4647 FINISHED
Object Peize E626186 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: Peize | Statement: [Hoogkerk, hasNeighbouringSettlement, Peize]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peize
Context triple: [Hoogkerk, hasNeighbouringSettlement, Peize]
  • A. Peize chosen
    Peize is a village in the Dutch province of Drenthe, known for its rural character and location within the municipality of Noordenveld.
  • B. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • C. Saussignac
    Saussignac is a small wine-producing commune in southwestern France, known for its sweet white wines made primarily from Sémillon and other Bordeaux grape varieties.
  • D. Patouès
    Patouès is a regional Romance dialect of the Franco-Provençal language traditionally spoken in parts of France, Switzerland, and Italy.
  • E. Yssingeaux
    Yssingeaux is a commune in south-central France that serves as an administrative and service center in the Haute-Loire department.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d747002b3081908726901ee83d8f38 completed April 9, 2026, 6:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d6c077608190822d66b23866f5eb completed April 18, 2026, 12:56 a.m.
Created at: April 8, 2026, 9:19 p.m.