Triple
T3014879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schlieren |
E82313
|
entity |
| Predicate | canton |
P3942
|
FINISHED |
| Object | Zürich |
E13407
|
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: Zürich | Statement: [Schlieren, canton, Zürich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zürich Context triple: [Schlieren, canton, Zürich]
-
A.
Zurich
chosen
Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
-
B.
Basel-Stadt
Basel-Stadt is a small, urban Swiss canton centered on the city of Basel, a major cultural and economic hub in northwestern Switzerland.
-
C.
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.
-
D.
Kloten
Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
-
E.
Geneva
Geneva is a major Swiss city on Lake Geneva known for hosting numerous international organizations, including United Nations agencies and the Red Cross.
- 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_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_69beba392ad08190a66ccf58edecb722 |
completed | March 21, 2026, 3:33 p.m. |
Created at: March 8, 2026, 3 p.m.