Triple
T6375366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Flanders |
E143452
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bailleul |
E434798
|
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: Bailleul | Statement: [French Flanders, contains, Bailleul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bailleul Context triple: [French Flanders, contains, Bailleul]
-
A.
Yvetot
Yvetot is a small town in the Seine-Maritime department of Normandy in northern France, historically known as the seat of a medieval "kingdom" within France.
-
B.
Cabourg
Cabourg is a seaside resort town in northwestern France, known for its Belle Époque architecture, sandy beaches, and association with writer Marcel Proust.
-
C.
Valognes
Valognes is a historic town in northwestern France known for its elegant 17th- and 18th-century mansions and its location on the Cotentin Peninsula in Normandy.
-
D.
Aire-sur-la-Lys
chosen
Aire-sur-la-Lys is a historic town in northern France’s Pas-de-Calais department, known for its medieval architecture and strategic location near the Lys River.
-
E.
Boulogne-sur-Mer
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.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0683ab8e08190ab3c9a5000b1d2be |
completed | March 22, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62d9dd9dc8190b2aca25feda3e690 |
completed | March 27, 2026, 7:11 a.m. |
Created at: March 22, 2026, 4:33 p.m.