Triple
T5134466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duchy of Aquitaine |
E115785
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Angoumois |
E149330
|
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: Angoumois | Statement: [Duchy of Aquitaine, contains, Angoumois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angoumois Context triple: [Duchy of Aquitaine, contains, Angoumois]
-
A.
Angoumois
chosen
Angoumois is a historic province in western France centered around the town of Angoulême, known for its role in the old French provincial system.
-
B.
Moulinois
Moulinois is the French term for an inhabitant or native of the town of Moulins in central France.
-
C.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
D.
Tignère
Tignère is a town and commune located in Cameroon's Adamawa Region, known for its highland setting and role as a local administrative and trading center.
-
E.
Lauzerte
Lauzerte is a medieval hilltop village in southern France known for its well-preserved historic center and picturesque views over the surrounding countryside.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd784e306081908dd8317227227807 |
completed | March 20, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec4cd5e188190b1404cefc887e0b3 |
completed | March 21, 2026, 4:18 p.m. |
Created at: March 20, 2026, 1:43 p.m.