Triple
T16993711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robots |
E412259
|
entity |
| Predicate | voiceCastMember |
P9616
|
FINISHED |
| Object | Dianne Wiest |
E38535
|
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: Dianne Wiest | Statement: [Robots, voiceCastMember, Dianne Wiest]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dianne Wiest Context triple: [Robots, voiceCastMember, Dianne Wiest]
-
A.
Dianne Wiest
chosen
Dianne Wiest is an acclaimed American actress known for her versatile performances in film, television, and theater, including multiple award-winning supporting roles.
-
B.
Jessica Walter
Jessica Walter was an American actress best known for her sharp, comedic portrayal of Lucille Bluth on the television series "Arrested Development."
-
C.
Shirley Heath
Shirley Heath is a large open heathland and recreational green space located in the Shirley area of the West Midlands, England.
-
D.
Stockard Channing
Stockard Channing is an American actress best known for her roles as Rizzo in the film "Grease" and First Lady Abbey Bartlet on the television series "The West Wing."
-
E.
Linda Purl
Linda Purl is an American actress and singer best known for her roles on television series such as "Happy Days," "Matlock," and "The Office."
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d28535788190bdfcb6201a9024b5 |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fb99b348190a6db655cd8aee799 |
completed | May 11, 2026, 4:48 a.m. |
Created at: April 10, 2026, 5:32 a.m.