Triple
T19489653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wetzikon |
E487613
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | Hinwil |
—
|
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: Hinwil | Statement: [Wetzikon, district, Hinwil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hinwil Context triple: [Wetzikon, district, Hinwil]
-
A.
Hinwil
chosen
Hinwil is a municipality and regional center in the Swiss canton of Zürich, known for its rural surroundings and as the home base of the Sauber Formula One team.
-
B.
Landiswil
Landiswil is a small rural municipality in the canton of Bern, Switzerland, characterized by its agricultural landscape and location in the Emmental region.
-
C.
Hergiswil
Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
-
D.
Dietlikon
Dietlikon is a municipality in the canton of Zurich in northern Switzerland, known for its residential areas and commercial zones within the Zurich metropolitan region.
-
E.
Richterswil
Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6348ad4088190b530f47efca90165 |
completed | April 20, 2026, 2:13 p.m. |
Created at: April 10, 2026, 1:39 p.m.