Triple
T20366635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcelle Dupont |
E496926
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marcelle |
—
|
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: Marcelle | Statement: [Marcelle Dupont, givenName, Marcelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcelle Context triple: [Marcelle Dupont, givenName, Marcelle]
-
A.
Marcelle
chosen
Marcelle is a given name, typically a feminine form of Marcel, used in various cultures.
-
B.
Arabelle
Arabelle is a feminine given name, typically considered a variant of Arabella, used in various English-speaking and European cultures.
-
C.
Chantal
Chantal is a commune located in the Sud Department of Haiti.
-
D.
Chantal
Chantal is the central protagonist of the animated series "High Seas," around whom the show's main adventures and storylines revolve.
-
E.
Martine
Martine is a feminine given name commonly used in French- and English-speaking countries.
- 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_69e0b4a4f9b081908a5a021919c21ccb |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67871bfdc8190948c46497cd675c9 |
completed | April 20, 2026, 7:03 p.m. |
Created at: April 16, 2026, 11:26 a.m.