Triple
T7181913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gelsenkirchen |
E167466
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Boulogne-sur-Mer |
E122723
|
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: Boulogne-sur-Mer | Statement: [Gelsenkirchen, twinTown, Boulogne-sur-Mer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boulogne-sur-Mer Context triple: [Gelsenkirchen, twinTown, Boulogne-sur-Mer]
-
A.
Boulogne-sur-Mer
chosen
Boulogne-sur-Mer is a coastal city and major fishing port in northern France, located on the English Channel in the Pas-de-Calais department.
-
B.
Boulogne
Boulogne is a French football club known for being one of the early professional teams in N’Golo Kanté’s career.
-
C.
Boulogne-sur-Seine
Boulogne-sur-Seine was a former commune in the western suburbs of Paris, France, now part of Boulogne-Billancourt, known historically as a residential and industrial area along the Seine River.
-
D.
Bény-sur-Mer
Bény-sur-Mer is a small commune in the Calvados department of Normandy in northwestern France, near the historic D-Day landing beaches.
-
E.
Montreuil-sur-Mer
Montreuil-sur-Mer is a small historic town in northern France, notably serving as a key setting in Victor Hugo’s novel "Les Misérables."
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8bc25088190a7d7f3ba2461b5e9 |
completed | March 27, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8342a44a08190abee47cc7482c757 |
completed | March 28, 2026, 8:03 p.m. |
Created at: March 27, 2026, 2:49 p.m.