Triple
T6126270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joy |
E136603
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Virginia Madsen |
E415997
|
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: Virginia Madsen | Statement: [Joy, starring, Virginia Madsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Virginia Madsen Context triple: [Joy, starring, Virginia Madsen]
-
A.
Virginia Madsen
chosen
Virginia Madsen is an American actress known for her versatile film and television roles, including acclaimed performances in movies such as "Sideways" and "Candyman."
-
B.
Samantha Morton
Samantha Morton is an acclaimed English actress and director known for her intense, emotionally rich performances in independent films and major productions alike.
-
C.
Téa Leoni
Téa Leoni is an American actress and producer best known for her leading roles in film and television, including the political drama series "Madam Secretary."
-
D.
Jorja Fox
Jorja Fox is an American actress best known for her long-running role as Sara Sidle on the television series CSI: Crime Scene Investigation.
-
E.
Tyne Daly
Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
- 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_69c008a0a37c81908e5b4f879158afb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c28dbbc8190a0a0c20ec794e81a |
completed | March 22, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d5f60848190bd75dfefa27b3315 |
completed | March 24, 2026, 4:04 a.m. |
Created at: March 22, 2026, 4:15 p.m.