Triple
T18160575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcellin Desboutin |
E434747
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marcellin |
—
|
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: Marcellin | Statement: [Marcellin Desboutin, givenName, Marcellin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcellin Context triple: [Marcellin Desboutin, givenName, Marcellin]
-
A.
Marcellin
chosen
Marcellin is a masculine given name most notably borne by Saint Marcellin Champagnat, the French priest who founded the Marist Brothers.
-
B.
Marcelin
Marcelin is a French diminutive form of the given name Marcel, often used as an affectionate or familiar variant.
-
C.
Guerin
Guerin is a surname of French origin borne by various notable individuals across fields such as arts, sports, and public life.
-
D.
Béraud
Béraud is a French surname most notably associated with the 19th-century painter Jean Béraud, renowned for his vivid depictions of Parisian life during the Belle Époque.
-
E.
Tanguy
Tanguy is a French surname most notably associated with Yves Tanguy, a prominent 20th-century Surrealist painter.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec21e6081909070491f679c873c |
completed | April 19, 2026, 1:55 p.m. |
Created at: April 10, 2026, 10:30 a.m.