Triple
T7468721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wels |
E176447
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Linz |
E75219
|
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: Linz | Statement: [Wels, locatedNear, Linz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linz Context triple: [Wels, locatedNear, Linz]
-
A.
Linz
chosen
Linz is a major Austrian city known for its industrial heritage, vibrant cultural scene, and location along the Danube River.
-
B.
Klagenfurt
Klagenfurt is the capital city of the Austrian state of Carinthia, known for its historic old town and proximity to Lake Wörthersee.
-
C.
St. Pölten
St. Pölten is the capital city of the Austrian state of Lower Austria, known for its baroque architecture and role as a regional administrative and cultural center.
-
D.
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.
-
E.
Wien
Wien is a German surname most notably borne by physicist Wilhelm Wien, known for his work on blackbody radiation and Wien's displacement law.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3f6f23881908e3e80b0c7335a15 |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89a712fdc8190998d9a05dc73f40c |
completed | March 29, 2026, 3:20 a.m. |
Created at: March 27, 2026, 3:40 p.m.