Triple
T4571469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Léon Azéma |
E123039
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Azéma
Azéma is a French surname most notably borne by architect Léon Azéma, known for his contributions to early 20th-century French public architecture.
|
E454185
|
NE FINISHED |
How this triple was built (4 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.
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.
-
B.
Margeride
Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
-
C.
Méjanelle
Méjanelle is a French wine-producing area recognized as a subregion within the broader Languedoc appellation in southern France.
-
D.
Fatoua
Fatoua is a small genus of flowering plants in the mulberry family, known for herbaceous species native to parts of Asia and the Pacific.
-
E.
Temara
Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Azéma Triple: [Léon Azéma, familyName, Azéma]
Generated description
Azéma is a French surname most notably borne by architect Léon Azéma, known for his contributions to early 20th-century French public architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Azéma Target entity description: Azéma is a French surname most notably borne by architect Léon Azéma, known for his contributions to early 20th-century French public architecture.
-
A.
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.
-
B.
Margeride
Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
-
C.
Méjanelle
Méjanelle is a French wine-producing area recognized as a subregion within the broader Languedoc appellation in southern France.
-
D.
Fatoua
Fatoua is a small genus of flowering plants in the mulberry family, known for herbaceous species native to parts of Asia and the Pacific.
-
E.
Temara
Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
- F. None of above. chosen
Provenance (5 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c5afa48190bb8505e2cc16e89f |
completed | March 20, 2026, 2:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd3cf5e10819099b2927c6f571673 |
completed | March 20, 2026, 11:10 p.m. |
| NEDg | Description generation | batch_69bdd7f1efd0819089410e63f853175b |
completed | March 20, 2026, 11:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdd86be2c48190af8011a983f26b0d |
completed | March 20, 2026, 11:29 p.m. |
Created at: March 20, 2026, 1:10 p.m.