Triple
T1092082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biel/Bienne |
E24186
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Biel (German) |
E24186
|
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: Biel (German) | Statement: [Biel/Bienne, hasNameInLanguage, Biel (German)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biel (German) Context triple: [Biel/Bienne, hasNameInLanguage, Biel (German)]
-
A.
Biel/Bienne
chosen
Biel/Bienne is a bilingual (German-French) Swiss city in the canton of Bern, known for its watchmaking industry and location at the eastern end of Lake Biel.
-
B.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
-
C.
Bütgenbach
Bütgenbach is a municipality in eastern Belgium’s German-speaking Community, known for its scenic lake, outdoor recreation, and proximity to the strategic Elsenborn Ridge.
-
D.
Berner
A Berner is a resident or native of the Swiss city of Bern.
-
E.
Breselenz
Breselenz is a small village in Lower Saxony, Germany, best known as the birthplace of the mathematician Bernhard Riemann.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b982018481908b222df095e318c0 |
completed | March 1, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c2a20b48190b3a550f6e5ee13e1 |
completed | March 7, 2026, 4:02 p.m. |
Created at: March 1, 2026, 7:42 p.m.