Triple
T2829929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longwy |
E62210
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Pétange |
E325804
|
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: Pétange | Statement: [Longwy, twinnedWith, Pétange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pétange Context triple: [Longwy, twinnedWith, Pétange]
-
A.
Pétange
chosen
Pétange is a commune in southwestern Luxembourg known for its proximity to the borders with Belgium and France and its role as a local transport and industrial hub.
-
B.
Sarreguemines
Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
-
C.
Verviers
Verviers is a city in eastern Belgium known historically for its textile industry and as a regional center in the province of Liège.
-
D.
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.
-
E.
Binche
Binche is a historic town in the Walloon region of Belgium, renowned for its well-preserved medieval architecture and its UNESCO-recognized Carnival of Binche.
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebbde4881908dfa78e28c7018e0 |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24af876288190ae21a1f434768e0d |
completed | March 12, 2026, 5:11 a.m. |
Created at: March 6, 2026, 10:01 p.m.