Triple

T20302751
Position Surface form Disambiguated ID Type / Status
Subject Schoonaarde E505523 entity
Predicate locatedNear P294 FINISHED
Object Wichelen 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: Wichelen | Statement: [Schoonaarde, locatedNear, Wichelen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wichelen
Context triple: [Schoonaarde, locatedNear, Wichelen]
  • A. Wichelen chosen
    Wichelen is a municipality in East Flanders, Belgium, situated along the River Scheldt and known for its rural character and natural floodplain landscapes.
  • B. Schussen
    The Schussen is a river in the German state of Baden-Württemberg that flows through the Upper Swabia region before emptying into Lake Constance.
  • C. Cartwheel
    Cartwheel was a major World War II Allied military campaign in the Pacific aimed at isolating and neutralizing the Japanese stronghold of Rabaul through a series of coordinated offensives.
  • D. Rütschelen
    Rütschelen is a small municipality in the canton of Bern in Switzerland.
  • E. Shimmy
    Shimmy is a software tool developed under the Farama Foundation ecosystem, likely related to reinforcement learning or simulation environments.
  • 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_69e0b4b8ab648190906e18538c250148 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6773e0864819095d272659cd2074d completed April 20, 2026, 6:58 p.m.
Created at: April 16, 2026, 11:17 a.m.