Triple
T17472002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kloten |
E425440
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | Bülach |
—
|
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: Bülach | Statement: [Kloten, district, Bülach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bülach Context triple: [Kloten, district, Bülach]
-
A.
Bülach
chosen
Bülach is a town in northern Switzerland that serves as a regional center near Zurich, known for its residential character and proximity to Zurich Airport.
-
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.
Uzwil
Uzwil is a municipality in the canton of St. Gallen in northeastern Switzerland, known as a regional industrial and residential center.
-
D.
Hergiswil
Hergiswil is a Swiss lakeside municipality known for its scenic setting on Lake Lucerne and its historic glassworks.
-
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 (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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451b8a51081908d94bebe2417e3d3 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.