Triple
T6746137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arlon |
E154217
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Sankt-Vith |
E8397
|
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: Sankt-Vith | Statement: [Arlon, hasTwinTown, Sankt-Vith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sankt-Vith Context triple: [Arlon, hasTwinTown, Sankt-Vith]
-
A.
St. Vith
chosen
St. Vith is a town in eastern Belgium that became a strategically important battleground during World War II, particularly noted for its role in the Battle of the Bulge.
-
B.
Hazebrouck
Hazebrouck is a commune in northern France known as a local commercial and transport hub within the historical region of French Flanders.
-
C.
Kanegem
Kanegem is a small village in West Flanders, Belgium, known for its historic church and rural character.
-
D.
Lannesdorf
Lannesdorf is a residential subdistrict of the Bad Godesberg borough in the city of Bonn, Germany.
-
E.
Blegny
Blegny is a municipality in eastern Belgium known for its historic coal mining heritage and rural character.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1b8a0f0819086b802983e8ffcb6 |
completed | March 27, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712a4de8c819090bdc94529f4f9d8 |
completed | March 27, 2026, 11:28 p.m. |
Created at: March 27, 2026, 2:10 p.m.