Triple
T13406876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buchs SG |
E319981
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Werdenberg |
E960894
|
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: Werdenberg | Statement: [Buchs SG, region, Werdenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Werdenberg Context triple: [Buchs SG, region, Werdenberg]
-
A.
Werdenberg
chosen
Werdenberg is a region in the Swiss canton of St. Gallen, known for its historic town and castle near the Rhine Valley.
-
B.
Sampaio
Sampaio is a Portuguese surname borne by various notable figures in fields such as politics, sports, and entertainment.
-
C.
Dos Santos
Dos Santos is a common Portuguese-language surname, especially prevalent in Brazil and other Lusophone countries.
-
D.
Cardoso
Cardoso is a common Portuguese-language surname borne by numerous individuals, including prominent Brazilian political and cultural figures.
-
E.
Vilhena
Vilhena is a municipality in the southern part of the Brazilian state of Rondônia, known as an important regional agricultural and commercial center.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4be498819094798473a1bfd853 |
completed | April 12, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7307ad4448190b4fb99abcc00430b |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:35 p.m.