Triple
T6749862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empa |
E154315
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Dübendorf |
E435587
|
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: Dübendorf | Statement: [Empa, locatedIn, Dübendorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dübendorf Context triple: [Empa, locatedIn, Dübendorf]
-
A.
Dübendorf
chosen
Dübendorf is a municipality in the canton of Zurich, Switzerland, known for its proximity to Zurich and its historic military and aviation facilities.
-
B.
Zurich Wiedikon
Zurich Wiedikon is a residential and commercial district in the city of Zurich, Switzerland, known for its urban character, good public transport connections, and proximity to the Sihl River.
-
C.
Kloten
Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
-
D.
Wetzikon
Wetzikon is a municipality and regional center in the canton of Zürich in Switzerland, known for its mix of residential areas, industry, and proximity to Lake Pfäffikon.
-
E.
Opfikon
Opfikon is a municipality in the canton of Zürich in Switzerland, known for its proximity to Zurich Airport and its role as a residential and commercial suburb of the city of Zürich.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1da32108190882949aa329d2b60 |
completed | March 27, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7510b2ad88190a48ce74631d321e6 |
completed | March 28, 2026, 3:54 a.m. |
Created at: March 27, 2026, 2:11 p.m.