Triple
T11973047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Traunviertel |
E284967
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Mostviertel |
E228789
|
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: Mostviertel | Statement: [Traunviertel, borders, Mostviertel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mostviertel Context triple: [Traunviertel, borders, Mostviertel]
-
A.
Mostviertel
chosen
Mostviertel is a picturesque region in southwestern Lower Austria known for its rolling hills, orchards, and traditional pear cider (Most) production.
-
B.
Innviertel
Innviertel is a historical and cultural region in western Upper Austria known for its rural landscapes, Baroque architecture, and strong Bavarian influences.
-
C.
Lichtensteig
Lichtensteig is a small historic town in the canton of St. Gallen in northeastern Switzerland, known for its well-preserved old town and picturesque setting in the Toggenburg region.
-
D.
Untereggen
Untereggen is a small Swiss municipality in the canton of St. Gallen, known for its rural character and location in the country’s northeastern region.
-
E.
Waltershof
Waltershof is an industrial and port district of Hamburg, Germany, located within the borough of Hamburg-Mitte.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9039107e48190ae4c4efd6257dd3c |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4597cf818819089b0d897c236b87b |
completed | May 1, 2026, 7:42 a.m. |
Created at: April 8, 2026, 9:46 p.m.