Triple
T22950159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longuyon |
E569990
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Bissen |
—
|
NE NERFINISHED |
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: Bissen | Statement: [Longuyon, twinnedWith, Bissen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bissen Context triple: [Longuyon, twinnedWith, Bissen]
-
A.
Bissen
chosen
Bissen is a commune in central Luxembourg known for its rural character and proximity to major industrial and transport hubs.
-
B.
Biss
Biss is the surname of American pianist and writer Jonathan Biss, known for his interpretations of Beethoven and other classical composers.
-
C.
Baflo
Baflo is a village in the Dutch province of Groningen, known for its historic church and rural character.
-
D.
Bulzi
Bulzi is a small town and comune in the province of Sassari on the Italian island of Sardinia.
-
E.
Chienbäse
Chienbäse is a traditional Swiss fire parade in Liestal, where participants carry burning bundles of pinewood and other fiery structures through the town to celebrate the pre-Lenten carnival season.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181a085188190b06ffa227087302d |
completed | April 29, 2026, 3:57 a.m. |
Created at: April 17, 2026, 3:46 p.m.