Triple
T2544136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Austria |
E57855
|
entity |
| Predicate | hasIndustrialCenter |
P3436
|
FINISHED |
| Object | Wels |
E176447
|
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: Wels | Statement: [Upper Austria, hasIndustrialCenter, Wels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wels Context triple: [Upper Austria, hasIndustrialCenter, Wels]
-
A.
Wels
chosen
Wels is a historic city in Upper Austria known as a former imperial residence and regional economic center.
-
B.
Bregenz
Bregenz is an Austrian city on the eastern shore of Lake Constance, known for its lakeside setting, cultural festivals, and contemporary art and architecture.
-
C.
Salzburg
Salzburg is a historic Austrian city on the Salzach River, renowned for its baroque architecture, Alpine setting, and as the birthplace of composer Wolfgang Amadeus Mozart.
-
D.
Innsbruck
Innsbruck is a city in western Austria known for its Alpine setting and winter sports facilities, and it later successfully hosted the Winter Olympics in 1964 and 1976.
-
E.
Kufstein
Kufstein is a historic town in the Austrian state of Tyrol, known for its medieval fortress and picturesque setting in the Alps near the German border.
- 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_69ab4a5212d88190b989ce129f2ad87f |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2c10ce88190b242ab3d41878fda |
completed | March 7, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afbbaef55881909ef223f366c209c7 |
completed | March 10, 2026, 6:35 a.m. |
Created at: March 6, 2026, 9:47 p.m.