Triple
T20644859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gmunden District |
E507327
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Altmünster |
—
|
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: Altmünster | Statement: [Gmunden District, containsMunicipality, Altmünster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altmünster Context triple: [Gmunden District, containsMunicipality, Altmünster]
-
A.
Altmünster
chosen
Altmünster is a market town in Upper Austria, situated on the shores of Lake Traunsee and known for its scenic Alpine surroundings.
-
B.
Altenmünster
Altenmünster is a municipality in the Swabian region of Bavaria, Germany, known for its rural character and location within the Augsburg district.
-
C.
Weilmünster
Weilmünster is a municipality in the Limburg-Weilburg district of Hesse, Germany, known for its rural character and location in the Lahn valley region.
-
D.
Münnerstadt
Münnerstadt is a historic small town in northern Bavaria, Germany, known for its well-preserved medieval architecture and location in the spa region of Lower Franconia.
-
E.
Altenau
Altenau is a small town in Germany’s Harz Mountains, historically known as a mining and spa resort surrounded by dense forests and mountain landscapes.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1d0be481909e090193dcfd9cf6 |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.