Triple

T3700342
Position Surface form Disambiguated ID Type / Status
Subject Sihl River E78561 entity
Predicate nearbyCity P350 FINISHED
Object Thalwil E415333 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: Thalwil | Statement: [Sihl River, nearbyCity, Thalwil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thalwil
Context triple: [Sihl River, nearbyCity, Thalwil]
  • A. Thalwil chosen
    Thalwil is a municipality in the canton of Zurich, Switzerland, known as a residential and commuter town situated on the western shore of Lake Zurich.
  • 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. 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.
  • D. Kloten
    Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
  • E. Kilchberg
    Kilchberg is a municipality on the shores of Lake Zurich in Switzerland, known for its scenic residential character and as the home of the Lindt & Sprüngli chocolate factory.
  • 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_69ad85e3b1888190abc983e06968696d completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc514eb6c8190b3b74a603c717729 completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d03dbd348190aaaa58a352982248 completed March 14, 2026, 9:16 p.m.
Created at: March 8, 2026, 3:26 p.m.