Triple
T21000407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lüterkofen-Ichertswil |
E517269
|
entity |
| Predicate | hasLocality |
P7943
|
FINISHED |
| Object | Lüterkofen |
—
|
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: Lüterkofen | Statement: [Lüterkofen-Ichertswil, hasLocality, Lüterkofen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lüterkofen Context triple: [Lüterkofen-Ichertswil, hasLocality, Lüterkofen]
-
A.
Lüterkofen
chosen
Lüterkofen is a village and former municipality in the canton of Solothurn in Switzerland.
-
B.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
-
C.
Gersthofen
Gersthofen is a town in Bavaria, Germany, located just north of Augsburg and known for its industrial presence and role as a regional transport hub.
-
D.
Lauterhofen
Lauterhofen is a market town in Bavaria, Germany, known for its rural character and location within the Upper Palatinate region.
-
E.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
- 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_69e0b5006e2881909fc2383f841740cc |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc24a6dc8190a6bf81cf1d9590c0 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:52 p.m.