Triple
T26774369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilles Lellouche |
E670075
|
entity |
| Predicate | hasFrenchWikipediaPage |
P162177
|
FINISHED |
| Object | https://fr.wikipedia.org/wiki/Gilles_Lellouche |
—
|
LITERAL 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: https://fr.wikipedia.org/wiki/Gilles_Lellouche | Statement: [Gilles Lellouche, hasFrenchWikipediaPage, https://fr.wikipedia.org/wiki/Gilles_Lellouche]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrenchWikipediaPage Context triple: [Gilles Lellouche, hasFrenchWikipediaPage, https://fr.wikipedia.org/wiki/Gilles_Lellouche]
-
A.
hasEnglishWikipediaArticle
Indicates that there exists an article about the subject in the English-language edition of Wikipedia.
-
B.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
C.
nameInFrench
Indicates that an entity is known or referred to by a specific name expressed in the French language.
-
D.
hasFrenchSector
Indicates that an entity includes, controls, or is associated with a sector or area designated as French.
-
E.
hasNameInWalloon
Indicates that an entity is associated with a specific name expressed in the Walloon language.
- F. None of above. chosen
Provenance (4 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f622abdfac8190988421c946411d7e |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620debeb48190b7db395fb86cf8d9 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621fbfc2c8190bfa802d7dc0f6aa4 |
completed | May 2, 2026, 4:10 p.m. |
Created at: April 27, 2026, 4:03 a.m.