Triple

T3644084
Position Surface form Disambiguated ID Type / Status
Subject Weil der Stadt E77255 entity
Predicate hasSubdivision P747 FINISHED
Object Schafhausen
Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
E443361 NE FINISHED

How this triple was built (4 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: Schafhausen | Statement: [Weil der Stadt, hasSubdivision, Schafhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schafhausen
Context triple: [Weil der Stadt, hasSubdivision, Schafhausen]
  • A. Schaffhausen
    Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
  • B. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • C. Solothurn
    Solothurn is a canton in northwestern Switzerland known for its historic baroque town of the same name and its location along the Aare River.
  • D. Adliswil
    Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
  • E. Rapperswil-Jona
    Rapperswil-Jona is a Swiss town in the canton of St. Gallen known for its historic old town, lakeside location, and prominent medieval castle.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Schafhausen
Triple: [Weil der Stadt, hasSubdivision, Schafhausen]
Generated description
Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Schafhausen
Target entity description: Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
  • A. Schaffhausen
    Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
  • B. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • C. Solothurn
    Solothurn is a canton in northwestern Switzerland known for its historic baroque town of the same name and its location along the Aare River.
  • D. Adliswil
    Adliswil is a municipality in the canton of Zurich, Switzerland, situated in the Sihl Valley just south of the city of Zurich.
  • E. Rapperswil-Jona
    Rapperswil-Jona is a Swiss town in the canton of St. Gallen known for its historic old town, lakeside location, and prominent medieval castle.
  • F. None of above. chosen

Provenance (5 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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc35c28908190b253f4835918a2b4 completed March 8, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69b63702874881909610763d5a48b09d completed March 15, 2026, 4:35 a.m.
NEDg Description generation batch_69b63823c30c8190af727acae00da9d3 completed March 15, 2026, 4:40 a.m.
NED2 Entity disambiguation (via description) batch_69b638a398f88190bd0f041e9494aeba completed March 15, 2026, 4:42 a.m.
Created at: March 8, 2026, 3:24 p.m.