Triple
T15922182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippe Amaury |
E386118
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Amaury |
E671297
|
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: Amaury | Statement: [Philippe Amaury, familyName, Amaury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amaury Context triple: [Philippe Amaury, familyName, Amaury]
-
A.
Amaury
chosen
Amaury is a masculine given name of French origin, historically borne by several medieval nobles and knights.
-
B.
Arnaud
Arnaud is a small commune located in Haiti’s Nippes Department.
-
C.
Arnaud Decagny
Arnaud Decagny is a French local politician who serves as the mayor of the northern town of Maubeuge.
-
D.
Arnaud-Guilhem
Arnaud-Guilhem is a small commune in southwestern France, located in the Haute-Garonne department in the Occitanie region.
-
E.
Benjamin Massoubre
Benjamin Massoubre is a French film editor known for his work on acclaimed animated films, including the Oscar-winning short "Logorama."
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156825b1881908477ec93cc7b5f02 |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb5aba70c8190a74c45bce6f9b782 |
completed | May 9, 2026, 10:31 p.m. |
Created at: April 10, 2026, 4:52 a.m.