Triple
T3336795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limmat |
E70156
|
entity |
| Predicate | passesNear |
P416
|
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, passesNear, Dietikon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dietikon Context triple: [Limmat, passesNear, 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.
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.
Liestal
Liestal is a historic Swiss town in northwestern Switzerland that serves as the administrative and cultural center of the canton of Basel-Landschaft.
-
D.
Pratteln
Pratteln is a municipality in northern Switzerland that serves as a major residential and industrial center in the canton of Basel-Landschaft.
-
E.
Olten
Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
- 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_69ad85a24f208190bcf83131bfed3521 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1bad97481909359e914d44a1a74 |
completed | March 8, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56275e1708190aa4b02acebb978c6 |
completed | March 14, 2026, 1:28 p.m. |
Created at: March 8, 2026, 3:12 p.m.