Triple
T5247182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limmat River |
E118490
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Dietikon |
E392055
|
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: Dietikon | Statement: [Limmat River, flowsThrough, Dietikon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dietikon Context triple: [Limmat River, flowsThrough, Dietikon]
-
A.
Dietikon
chosen
Dietikon is a town and municipality in the canton of Zurich in Switzerland, known as an important regional center in the Limmat Valley.
-
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.
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.
-
E.
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.
- 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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b5320748190bcf3be4b6c364f92 |
completed | March 20, 2026, 4:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02777c0908190a0aebbbca3b7b0a6 |
completed | March 22, 2026, 5:31 p.m. |
Created at: March 20, 2026, 1:50 p.m.