Triple

T3014896
Position Surface form Disambiguated ID Type / Status
Subject Schlieren E82313 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Dietikon
Dietikon is a town and municipality in the canton of Zurich in Switzerland, known as an important regional center in the Limmat Valley.
 E392055 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: Dietikon | Statement: [Schlieren, neighboringMunicipality, Dietikon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dietikon
Context triple: [Schlieren, neighboringMunicipality, Dietikon]
  • A. 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.
  • B. Liestal
    Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
  • C. Pratteln
    Pratteln is a municipality in northern Switzerland that serves as a major residential and industrial center in the canton of Basel-Landschaft.
  • D. Olten
    Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
  • E. 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.
  • 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: Dietikon
Triple: [Schlieren, neighboringMunicipality, Dietikon]
Generated description
Dietikon is a town and municipality in the canton of Zurich in Switzerland, known as an important regional center in the Limmat Valley.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dietikon
Target entity description: Dietikon is a town and municipality in the canton of Zurich in Switzerland, known as an important regional center in the Limmat Valley.
  • A. 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.
  • B. Liestal
    Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
  • C. Pratteln
    Pratteln is a municipality in northern Switzerland that serves as a major residential and industrial center in the canton of Basel-Landschaft.
  • D. Olten
    Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
  • E. 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.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a69e8148190a97507740c9d26a8 completed March 8, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503d3f19c819088061d3c68757957 completed March 14, 2026, 6:44 a.m.
NEDg Description generation batch_69b50523dbb08190b1fd089092c1b2a6 completed March 14, 2026, 6:50 a.m.
NED2 Entity disambiguation (via description) batch_69b50594e4888190b2db45eee2a988a7 completed March 14, 2026, 6:52 a.m.
Created at: March 8, 2026, 3 p.m.