Triple
T21746947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foxy Brown |
E536813
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Marchand |
—
|
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: Marchand | Statement: [Foxy Brown, familyName, Marchand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marchand Context triple: [Foxy Brown, familyName, Marchand]
-
A.
Marchand
chosen
Marchand is the surname of American rapper and actress Foxy Brown, whose full name is Inga DeCarlo Fung Marchand.
-
B.
Henri Marchand
Henri Marchand was an actor known for appearing in the French film "Fanfare of Love."
-
C.
Monsieur Fleurant
Monsieur Fleurant is the apothecary in Molière’s comedy "The Imaginary Invalid," known for supplying Argan with an endless stream of medicines and treatments.
-
D.
Monsieur Dambreuse
Monsieur Dambreuse is a wealthy, influential bourgeois banker in Gustave Flaubert’s novel "Sentimental Education," embodying the political and social ambitions of the French upper middle class.
-
E.
Guy le Bouteiller
Guy le Bouteiller was a French military leader best known for commanding the defense of Rouen during the Hundred Years' War.
- 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a771b908190886cade242e263e4 |
completed | April 28, 2026, 2:24 a.m. |
Created at: April 16, 2026, 6:49 p.m.