Triple
T9999412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dana Brunetti |
E197284
|
entity |
| Predicate | businessPartner |
P282
|
FINISHED |
| Object | Kevin Spacey |
E90872
|
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: Kevin Spacey | Statement: [Dana Brunetti, businessPartner, Kevin Spacey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kevin Spacey Context triple: [Dana Brunetti, businessPartner, Kevin Spacey]
-
A.
Kevin Spacey
chosen
Kevin Spacey is an American actor known for his intense, often villainous roles in film and television, including acclaimed performances in "The Usual Suspects," "American Beauty," and "House of Cards."
-
B.
Brian Michael Cox
Brian Michael Cox is a Grammy-winning American songwriter and record producer known for his work on numerous R&B and pop hits.
-
C.
Michael York
Michael York is an English actor known for his roles in films such as "Cabaret," "Logan's Run," and the "Austin Powers" series.
-
D.
Ed Harris
Ed Harris is an American actor and filmmaker known for his intense, authoritative performances in films such as "The Truman Show," "Apollo 13," and "Pollock."
-
E.
Sam Waterston
Sam Waterston is an American actor known for his distinguished film, television, and stage career, including prominent roles in productions such as Law & Order and The Killing Fields.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8dc9c081909b6d20909ada09cf |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b5e243548190b77328b5ce9e8028 |
completed | April 5, 2026, 7:20 p.m. |
Created at: March 30, 2026, 8:51 p.m.