Triple
T19800518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denise Jackson |
E475659
|
entity |
| Predicate | hasFirstName |
P17
|
FINISHED |
| Object | Denise |
—
|
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: Denise | Statement: [Denise Jackson, hasFirstName, Denise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denise Context triple: [Denise Jackson, hasFirstName, Denise]
-
A.
Denise
Denise is the custom video display chip used in early Commodore Amiga computers, responsible for handling their advanced graphics and sprite capabilities.
-
B.
Denise
Denise is a central character in the comedy film "Hot Rod," serving as Rod Kimble's kind-hearted and supportive love interest.
-
C.
Denise
Denise is the given name of American businesswoman and NFL team owner Denise DeBartolo York.
-
D.
Denise
chosen
Denise is a feminine given name of French origin that became widely known in the English-speaking world through popular culture and television characters.
-
E.
Denise
Denise is a fictional character in Don DeLillo’s novel "White Noise," known as one of Jack Gladney’s perceptive and skeptical children.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653cb865c81909696d2b37476f62f |
completed | April 20, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:49 p.m.