Triple

T5021384
Position Surface form Disambiguated ID Type / Status
Subject Franeker E112857 entity
Predicate hasLandmark P105 FINISHED
Object Martinikerk Franeker E471605 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: Martinikerk Franeker | Statement: [Franeker, hasLandmark, Martinikerk Franeker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martinikerk Franeker
Context triple: [Franeker, hasLandmark, Martinikerk Franeker]
  • A. Scheemda
    Scheemda is a village in the municipality of Oldambt in the province of Groningen in the northeastern Netherlands.
  • B. Hoendiep
    Hoendiep is a canal in the Dutch province of Groningen that serves as an important regional waterway and transport route.
  • C. Franeker, Friesland, Netherlands chosen
    Franeker is a historic university town in the Dutch province of Friesland, known for its rich academic heritage and traditional Frisian culture.
  • D. Volendam
    Volendam is a traditional Dutch fishing village and popular tourist destination known for its historic harbor, wooden houses, and preserved local costumes.
  • E. Krabbendijke
    Krabbendijke is a village in the Dutch province of Zeeland, known for its agricultural surroundings and location on the former island of Zuid-Beveland.
  • 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_69bd4435c2f48190be593158cbfcf8a3 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73656edc8190b802ad38d9552b58 completed March 20, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69be927f4ad0819096826f6cb141c90b completed March 21, 2026, 12:43 p.m.
Created at: March 20, 2026, 1:36 p.m.