Triple
T18198051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mari Blanchard |
E435711
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Blanchard |
—
|
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: Blanchard | Statement: [Mari Blanchard, familyName, Blanchard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blanchard Context triple: [Mari Blanchard, familyName, Blanchard]
-
A.
Blanchard
chosen
Blanchard is a French surname borne by numerous notable figures, including economists, politicians, and artists.
-
B.
Leblanc
Leblanc is an alias used by Jean Valjean, the protagonist of Victor Hugo's novel "Les Misérables," to conceal his identity.
-
C.
Tremblay
Tremblay is a common French-Canadian surname, particularly prevalent in Quebec and associated with numerous public figures in sports, politics, and the arts.
-
D.
Bachardy
Bachardy is the surname of American portrait artist and writer Don Bachardy, known for his long partnership with author Christopher Isherwood.
-
E.
Aspremont
Aspremont is a small picturesque commune in southeastern France, situated in the hills above Nice in the Alpes-Maritimes department.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d47f1c819082eec59492497797 |
completed | April 19, 2026, 2:04 p.m. |
Created at: April 10, 2026, 10:31 a.m.