Triple
T19659031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Hunt |
E472027
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Karen Kline |
—
|
NE NERFINISHED |
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: Karen Kline | Statement: [Linda Hunt, spouse, Karen Kline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karen Kline Context triple: [Linda Hunt, spouse, Karen Kline]
-
A.
Karen Kline
chosen
Karen Kline is an American psychotherapist best known as the longtime spouse of Academy Award–winning actress Linda Hunt.
-
B.
Elisabeth Shue
Elisabeth Shue is an American actress known for her roles in films such as "The Karate Kid," "Adventures in Babysitting," and "Leaving Las Vegas," for which she received an Academy Award nomination.
-
C.
Danielle Kaye
Danielle Kaye is known as the spouse of British film director and music video creator Tony Kaye.
-
D.
Lindsay Crouse
Lindsay Crouse is an American actress known for her work in film, television, and theater, including an Academy Award–nominated role in "Places in the Heart."
-
E.
Candice Bergen
Candice Bergen is an American actress and former fashion model best known for her Emmy-winning role as the sharp-tongued journalist Murphy Brown on the hit television sitcom of the same name.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641485ce481908b3860fa5e3a9f6e |
completed | April 20, 2026, 3:07 p.m. |
Created at: April 10, 2026, 1:45 p.m.