Triple
T15403904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aisne |
E368397
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Vouziers |
E830424
|
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: Vouziers | Statement: [Aisne, passesThrough, Vouziers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vouziers Context triple: [Aisne, passesThrough, Vouziers]
-
A.
Vouziers
chosen
Vouziers is a small commune in northeastern France known for its historical role in World War I and its location in the rural Ardennes region.
-
B.
Vaujours
Vaujours is a small suburban commune in the northeastern outskirts of Paris, France.
-
C.
Tournan
Tournan is a suburban town in the Île-de-France region of France that serves as an outer terminus for Paris’s RER commuter rail network.
-
D.
Chiroubles
Chiroubles is a French appellation in the Beaujolais region known for producing light, aromatic red wines primarily from the Gamay grape.
-
E.
Calvé
Calvé is a well-known food brand, particularly recognized for its peanut butter and sauces, that forms part of Unilever’s global brand portfolio.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8fde64819082ec0c68df305561 |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f372f7c8190ba04b8bd13bff95c |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 3:19 a.m.