Triple
T1789453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commodore Amiga 2000 |
E39461
|
entity |
| Predicate | graphicsChip |
P20530
|
FINISHED |
| Object | Denise |
E214650
|
NE FINISHED |
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: [Commodore Amiga 2000, graphicsChip, Denise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denise Context triple: [Commodore Amiga 2000, graphicsChip, Denise]
-
A.
Denise
chosen
Denise is the custom video display chip used in early Commodore Amiga computers, responsible for handling their advanced graphics and sprite capabilities.
-
B.
Diane
Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
-
C.
Danielle
"Danielle" is a work created by Sarah Churchill, known as part of her contributions to the arts.
-
D.
Denise Mara
Denise Mara is the wife of New York Giants co-owner John Mara and a member of the prominent Mara family associated with the NFL franchise.
-
E.
Debra
Debra is a central character in Cory Doctorow's science fiction novel "Down and Out in the Magic Kingdom," set in a futuristic, reputation-based society at Disney World.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abaffee0f88190aa7a42ef4a4e2bd2 |
completed | March 7, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb9c69488190abcbbf796176fca5 |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 4, 2026, 7:32 p.m.