Triple
T11630367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonding |
E276379
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Pasching |
E540799
|
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: Pasching | Statement: [Leonding, borderedBy, Pasching]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasching Context triple: [Leonding, borderedBy, Pasching]
-
A.
Pasching
chosen
Pasching is a small municipality in Upper Austria, near Linz, known for its shopping centers and the Waldstadion football stadium.
-
B.
Schärding
Schärding is a historic Austrian town on the border with Germany, known for its well-preserved baroque old town and riverside setting.
-
C.
Vöcklabruck
Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
-
D.
Patersdorf
Patersdorf is a small municipality in the Bavarian Forest region of southeastern Germany.
-
E.
Traunkirchen
Traunkirchen is a picturesque lakeside village in Upper Austria, known for its scenic setting on Lake Traunsee and historic pilgrimage church.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a127b2688190ae3a340f851e834b |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a527dc08190a3ce08ddedaa5753 |
completed | May 2, 2026, 2:29 p.m. |
Created at: April 8, 2026, 9:39 p.m.