Triple
T3360227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Léon |
E70702
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Léon (with acute accent on e) |
E70702
|
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: Léon (with acute accent on e) | Statement: [Léon, hasVariant, Léon (with acute accent on e)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Léon (with acute accent on e) Context triple: [Léon, hasVariant, Léon (with acute accent on e)]
-
A.
Léonard
Léonard is a given name and surname used in French-speaking contexts, corresponding to the name Leonhard or Leonard.
-
B.
Eugène
Eugène is a masculine given name of French origin, derived from the Greek "Eugenios," meaning "well-born" or "noble."
-
C.
Léon
chosen
Léon is a French surname borne by various notable individuals across fields such as politics, arts, and academia.
-
D.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
-
E.
Laurent
Laurent is a Belgian prince, the younger son of King Albert II and Queen Paola, known for his environmental interests and occasional public controversies.
- 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_69ad85a660c48190998489309a3b4869 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb266c4a881908aded39ccb8f43b2 |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b32541ed808190aa7be7d0b7606426 |
completed | March 12, 2026, 8:42 p.m. |
Created at: March 8, 2026, 3:13 p.m.