Triple

T4888886
Position Surface form Disambiguated ID Type / Status
Subject Canton of Zürich E109508 entity
Predicate contains P35 FINISHED
Object Illnau-Effretikon
Illnau-Effretikon is a municipality in the canton of Zürich in Switzerland, known for its mix of suburban residential areas and rural landscapes.
 E497530 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: Illnau-Effretikon | Statement: [Canton of Zürich, contains, Illnau-Effretikon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Illnau-Effretikon
Context triple: [Canton of Zürich, contains, Illnau-Effretikon]
  • A. Neuenegg
    Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
  • 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. Richterswil
    Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
  • 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. Walchwil
    Walchwil is a picturesque Swiss municipality in the canton of Zug, known for its scenic location on the eastern shore of Lake Zug and views of the surrounding Alps.
  • 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: Illnau-Effretikon
Triple: [Canton of Zürich, contains, Illnau-Effretikon]
Generated description
Illnau-Effretikon is a municipality in the canton of Zürich in Switzerland, known for its mix of suburban residential areas and rural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Illnau-Effretikon
Target entity description: Illnau-Effretikon is a municipality in the canton of Zürich in Switzerland, known for its mix of suburban residential areas and rural landscapes.
  • A. Neuenegg
    Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
  • 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. Richterswil
    Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
  • 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. Walchwil
    Walchwil is a picturesque Swiss municipality in the canton of Zug, known for its scenic location on the eastern shore of Lake Zug and views of the surrounding Alps.
  • 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_69bd440f71348190b99938e59fb7f9a1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e06a81881908734dbdc350a2039 completed March 20, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfa0b4fc8190bf9ee8abf1684503 completed March 21, 2026, 5:04 p.m.
NEDg Description generation batch_69bed1d770a88190a3ff820ba878c8a2 completed March 21, 2026, 5:13 p.m.
NED2 Entity disambiguation (via description) batch_69bed2303df881908260b27d430f16fc completed March 21, 2026, 5:15 p.m.
Created at: March 20, 2026, 1:28 p.m.