Triple
T11323745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altmünster |
E268155
|
entity |
| Predicate | hasLakeShore |
P1025
|
FINISHED |
| Object | Traunsee |
E279839
|
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: Traunsee | Statement: [Altmünster, hasLakeShore, Traunsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Traunsee Context triple: [Altmünster, hasLakeShore, Traunsee]
-
A.
Traunsee
chosen
Traunsee is a picturesque alpine lake in Upper Austria, known for its deep waters, surrounding mountains, and popular lakeside towns like Gmunden.
-
B.
Traun River
The Traun River is a major tributary of the Danube in Austria, flowing through the Salzkammergut lake district and the state of Upper Austria.
-
C.
Eisack
Eisack is a major river in northern Italy that flows through the South Tyrol region, including the city of Bolzano, before joining the Adige.
-
D.
Traun
Traun is a town in the Austrian state of Upper Austria, located near Linz along the Traun River and known as a residential and industrial suburb of the regional capital.
-
E.
Traun
Traun is a river in southeastern Germany that flows through the Chiemgau region of Bavaria.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e122e48190b3f890de8d561480 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e543055b588190a417b3d50ade989a |
completed | April 19, 2026, 9:03 p.m. |
Created at: April 8, 2026, 9:32 p.m.