Triple
T19805019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echternach |
E475787
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Prüm |
—
|
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: Prüm | Statement: [Echternach, hasTwinTown, Prüm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prüm Context triple: [Echternach, hasTwinTown, Prüm]
-
A.
Prüm
chosen
Prüm is a historic town and former abbey center in the Eifel region of present-day Germany, known for its medieval religious and political significance.
-
B.
Grevenmacher
Grevenmacher is a town in eastern Luxembourg on the Moselle River, known as a regional wine-producing center and an important crossing point on the Germany–Luxembourg border.
-
C.
Nassau-Vianden
Nassau-Vianden was a historical county of the House of Nassau located around Vianden in present-day Luxembourg and Germany.
-
D.
Saarbrücken
Saarbrücken is a German city on the Saar River known as an industrial, cultural, and educational center near the French border.
-
E.
Diekirch
Diekirch is a town in northern Luxembourg known for its role in World War II, particularly during the country's liberation, and for its national military museum.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65427546c819082c8eb0d63e3f5fe |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.