Triple
T12566243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany–Luxembourg border |
E295484
|
entity |
| Predicate | hasBorderTown |
P847
|
FINISHED |
| Object | Wasserbillig |
E946790
|
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: Wasserbillig | Statement: [Germany–Luxembourg border, hasBorderTown, Wasserbillig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wasserbillig Context triple: [Germany–Luxembourg border, hasBorderTown, Wasserbillig]
-
A.
Wasserbillig
chosen
Wasserbillig is a town in eastern Luxembourg on the border with Germany, known as a key cross-border transport and railway junction.
-
B.
Wateren
Wateren is a small village in the Dutch province of Drenthe, known for its rural character and proximity to heathlands and forests.
-
C.
Landwasser
Landwasser is a river in the canton of Graubünden in eastern Switzerland that flows through the alpine town of Davos.
-
D.
Weener
Weener is a small town and municipality in the Leer district of Lower Saxony in northwestern Germany, known for its historic harbor and location on the River Ems.
-
E.
Gwäss
Gwäss is a traditional Central European white grape variety, better known under the name Heunisch Weiss, historically used in wine production for its high acidity and vigor.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9549611c081909e611756f3cce7f0 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6558f87b081909ba179b49bae3913 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:49 p.m.