Triple
T21752146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liliane Bettencourt |
E536940
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Schueller |
—
|
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: Schueller | Statement: [Liliane Bettencourt, familyName, Schueller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schueller Context triple: [Liliane Bettencourt, familyName, Schueller]
-
A.
Schueller
chosen
Schueller is a French surname most notably associated with Eugène Schueller, the chemist and entrepreneur who founded the cosmetics company L’Oréal.
-
B.
Gallaher
Gallaher is a surname of Irish origin borne by various notable individuals, including figures in sports, politics, and the arts.
-
C.
Seiberling
Seiberling is a surname most notably associated with American industrialist Frank Seiberling, co-founder of the Goodyear Tire & Rubber Company.
-
D.
Stauffer
Stauffer is a German-language surname borne by various notable individuals in fields such as music, politics, and academia.
-
E.
Schroda
Schroda is a town in western Poland, historically part of the Prussian Province of Posen, known today as Środa Wielkopolska.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8a6d4881908cc69e7247cce3a5 |
completed | April 28, 2026, 2:38 a.m. |
Created at: April 16, 2026, 6:50 p.m.