Triple
T21900679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gmünd District |
E540798
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Gmünd |
—
|
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: Gmünd | Statement: [Gmünd District, containsTown, Gmünd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gmünd Context triple: [Gmünd District, containsTown, Gmünd]
-
A.
Gmünd
chosen
Gmünd is a town in Lower Austria near the Czech border, known for its historic center and role as a regional transport and trade hub.
-
B.
Mauthen
Mauthen is a small village in the Austrian state of Carinthia, known for its Alpine setting near the Italian border.
-
C.
Sankt Veit an der Glan
Sankt Veit an der Glan is a historic town in the Austrian state of Carinthia, known for its medieval architecture and role as a former ducal residence.
-
D.
Schärding
Schärding is a historic Austrian town on the border with Germany, known for its well-preserved baroque old town and riverside setting.
-
E.
Gmunden
Gmunden is a picturesque town in Upper Austria known for its lakeside setting on the Traunsee and its historic ceramics industry.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fcb18748190a21071c122b7e6d5 |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:07 p.m.