Triple
T17142339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia Madsen |
E415997
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Michael Madsen |
E314429
|
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: Michael Madsen | Statement: [Virginia Madsen, sibling, Michael Madsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Madsen Context triple: [Virginia Madsen, sibling, Michael Madsen]
-
A.
Michael Madsen
chosen
Michael Madsen is an American actor known for his tough-guy roles in films such as Reservoir Dogs, Kill Bill, and other Quentin Tarantino movies.
-
B.
Charles Bronson
Charles Bronson was an American film actor best known for his tough-guy roles in action and Western movies, including the "Death Wish" series.
-
C.
Armand Assante
Armand Assante is an American actor known for his intense screen presence and roles in crime dramas and historical films.
-
D.
Cole Hauser
Cole Hauser is an American actor known for his tough, authoritative roles in films like "Dazed and Confused," "Pitch Black," and "2 Fast 2 Furious," as well as the TV series "Yellowstone."
-
E.
Robert Michael Ryan
Robert Michael Ryan is an actor best known for his role on the 1990s American teen sitcom "Hang Time."
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2d5de10819090cbd65661b018d3 |
completed | April 18, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a014154b9848190ac01602eb01ae710 |
completed | May 11, 2026, 2:39 a.m. |
Created at: April 10, 2026, 5:36 a.m.