Triple
T8521017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnus |
E201692
|
entity |
| Predicate | worksWith |
P398
|
FINISHED |
| Object | Denise |
unclear NED1
|
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: [Agnus, worksWith, Denise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Denise Context triple: [Agnus, worksWith, 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 Robert
Denise Robert is a Canadian film producer known for her work on acclaimed Quebec cinema, including collaborations with director Denys Arcand.
-
D.
Diane
Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
-
E.
Danielle
"Danielle" is a work created by Sarah Churchill, known as part of her contributions to the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe62a490481908ee0ad4ba9a94682 |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6d3fabb08190a3ad63f9153ad44c |
completed | April 2, 2026, 1:21 p.m. |
Created at: March 30, 2026, 6:16 p.m.