Triple
T18980183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seetal |
E464399
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Hochdorf |
—
|
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: Hochdorf | Statement: [Seetal, hasTown, Hochdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hochdorf Context triple: [Seetal, hasTown, Hochdorf]
-
A.
Hochdorf
chosen
Hochdorf is a municipality in the canton of Lucerne in central Switzerland, known as a regional center in the Seetal valley.
-
B.
Hochstetten
Hochstetten is a locality within the town of Breisach am Rhein in the Baden-Württemberg region of southwestern Germany.
-
C.
Hägendorf
Hägendorf is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Jura mountains.
-
D.
Oberhöchstadt
Oberhöchstadt is a district of the town of Kronberg im Taunus in Hesse, Germany, known for its residential character within the Taunus region.
-
E.
Grosshöchstetten
Grosshöchstetten is a municipality in the canton of Bern in Switzerland, known for its rural character and proximity to the city of Bern.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d65b573881908575e61a62b70787 |
completed | April 20, 2026, 7:31 a.m. |
Created at: April 10, 2026, 12:01 p.m.