Triple
T4938600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aisne-Marne American Cemetery |
E110872
|
entity |
| Predicate | department |
P1467
|
FINISHED |
| Object | Aisne |
E83838
|
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: Aisne | Statement: [Aisne-Marne American Cemetery, department, Aisne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aisne Context triple: [Aisne-Marne American Cemetery, department, Aisne]
-
A.
Aisne
chosen
Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
-
B.
Aisne
Aisne is a river in northeastern France that flows through the Champagne and Picardy regions before joining the Oise River.
-
C.
Marne
The Marne is a major river in northeastern France that flows through the Île-de-France region before joining the Seine near Paris.
-
D.
Oise-Aisne
Oise-Aisne is a region in northern France that was a major World War I battlefield, notably during the Aisne and Oise-Aisne offensives.
-
E.
Nièvre
Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7088f6e48190bf09e58ab053a4d1 |
completed | March 20, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c2437136f48190b34454ce77397daf |
completed | March 24, 2026, 7:55 a.m. |
Created at: March 20, 2026, 1:31 p.m.