Triple
T18583757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Léon Azéma |
E454185
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Azéma |
—
|
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: Azéma | Statement: [Léon Azéma, familyName, Azéma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Azéma Context triple: [Léon Azéma, familyName, Azéma]
-
A.
Azéma
chosen
Azéma is a French surname most notably borne by architect Léon Azéma, known for his contributions to early 20th-century French public architecture.
-
B.
Azema
Azema is a French surname and given name of Occitan origin, borne by various notable individuals in fields such as the arts and sciences.
-
C.
Aixa
Aixa was a prominent Nasrid noblewoman of the Emirate of Granada, best known as the politically influential mother of the last Muslim ruler of Granada, Boabdil.
-
D.
Azélie
Azélie is a short story by Kate Chopin, included in her 1897 collection *A Night in Acadie*, that explores themes of love, culture, and identity in a Louisiana setting.
-
E.
Landais
Landais is a regional variety of the Gascon Occitan language traditionally spoken in parts of southwestern France.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543d200dc8190b8797d731f4e4865 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 11:44 a.m.