Triple
T4036448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aisne |
E83838
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Soissons |
E448252
|
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: Soissons | Statement: [Aisne, contains, Soissons]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soissons Context triple: [Aisne, contains, Soissons]
-
A.
Soissons
chosen
Soissons is a historic town in northern France known for its strategic military importance and notable battles throughout European history.
-
B.
Poissy
Poissy is a commune in the western suburbs of Paris, France, known for hosting Le Corbusier’s iconic modernist Villa Savoye.
-
C.
Dourdan
Dourdan is a commune in the Essonne department in the southern suburbs of Paris, France, known for its historic medieval castle and role as a terminus on the RER C suburban rail line.
-
D.
Château-Thierry
Château-Thierry is a historic town in northern France known for its World War I battlefields and its association with the poet Jean de La Fontaine.
-
E.
Meaux
Meaux is a historic commune in the Île-de-France region of north-central France, known for its cathedral, World War I heritage, and production of Brie de Meaux cheese.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb349e648190b9f227df4cd76fa0 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf779f7d54819083e1cb88e34c6d34 |
completed | March 22, 2026, 5:01 a.m. |
Created at: March 9, 2026, 3:36 p.m.