Triple

T14252519
Position Surface form Disambiguated ID Type / Status
Subject Zwolle E353304 entity
Predicate hasLandmark P105 FINISHED
Object Sassenpoort E889437 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: Sassenpoort | Statement: [Zwolle, hasLandmark, Sassenpoort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sassenpoort
Context triple: [Zwolle, hasLandmark, Sassenpoort]
  • A. Sassenpoort chosen
    Sassenpoort is a well-preserved medieval city gate and former defensive tower in Zwolle, the Netherlands, notable for its Gothic architecture and historical significance.
  • B. Groothoofdspoort
    Groothoofdspoort is a historic city gate and waterfront landmark in Dordrecht, Netherlands, known for its picturesque location where several rivers meet.
  • C. Regulierspoort
    Regulierspoort was the original medieval city gate in Amsterdam whose remaining tower later became known as the Munttoren (Mint Tower).
  • D. Berkelpoort
    Berkelpoort is a historic medieval city gate in Zutphen, the Netherlands, that once formed part of the town’s defensive fortifications along the Berkel river.
  • E. Vischpoort
    Vischpoort is a historic city gate in Harderwijk, Netherlands, dating back to the Middle Ages and once part of the town’s defensive fortifications.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6297f38c819090d7c7fd8bfa2e9e completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd325a14b881909522b6fbbcc6326f completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:08 a.m.