Triple
T21746946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foxy Brown |
E536813
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Inga |
—
|
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: Inga | Statement: [Foxy Brown, givenName, Inga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inga Context triple: [Foxy Brown, givenName, Inga]
-
A.
Inga
chosen
Inga is the given first name of American rapper and actress Foxy Brown, whose full name is Inga DeCarlo Fung Marchand.
-
B.
Inga
Inga are an Indigenous people of the Andean region of Colombia, known for their Quechua-related language and rich traditions in agriculture, herbal medicine, and communal life.
-
C.
Inga
Inga is a comedic, good-natured lab assistant and love interest in Mel Brooks’s film "Young Frankenstein," known for her playful personality and memorable lines.
-
D.
Vouacapoua
Vouacapoua is a small genus of tropical leguminous trees in the family Fabaceae, known for their dense hardwood and occurrence in South American rainforests.
-
E.
Teregua
Teregua is a small locality or hamlet that forms part of the municipality of Valfurva in northern Italy’s Lombardy region.
- 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.