Triple
T22530786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plot B (Oise-Aisne American Cemetery) |
E557029
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Seringes-et-Nesles |
—
|
NE NERFINISHED |
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: Seringes-et-Nesles | Statement: [Plot B (Oise-Aisne American Cemetery), locatedNear, Seringes-et-Nesles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seringes-et-Nesles Context triple: [Plot B (Oise-Aisne American Cemetery), locatedNear, Seringes-et-Nesles]
-
A.
Seringes-et-Nesles
chosen
Seringes-et-Nesles is a commune in northern France notable for hosting the Oise-Aisne American Cemetery, a major World War I military burial ground.
-
B.
Les Essarts
Les Essarts is a small French commune located in the Loir-et-Cher department in central France.
-
C.
Léchelles
Léchelles is a village and former municipality in the canton of Fribourg in western Switzerland.
-
D.
Soignies
Soignies is a historic town and municipality in the province of Hainaut in Wallonia, Belgium, known for its medieval collegiate church and blue limestone industry.
-
E.
L’Arbresle
L’Arbresle is a small commune in eastern France’s Auvergne-Rhône-Alpes region, known for its historic town center and proximity to Lyon.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed6734881908abbbee477dfab98 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 16, 2026, 8:51 p.m.