Triple
T23207437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liv Lerner |
E580497
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Kate Hudson |
—
|
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: Kate Hudson | Statement: [Liv Lerner, portrayedBy, Kate Hudson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kate Hudson Context triple: [Liv Lerner, portrayedBy, Kate Hudson]
-
A.
Kate Hudson
chosen
Kate Hudson is an American actress known for her roles in romantic comedies and dramas, including her performance in the 2010 crime film "The Killer Inside Me."
-
B.
Jennifer Love Hewitt
Jennifer Love Hewitt is an American actress and singer best known for her roles in 1990s and 2000s film and television, including the horror and teen drama genres.
-
C.
Katherine Heigl
Katherine Heigl is an American actress and former fashion model best known for her roles in the television series "Grey's Anatomy" and various romantic comedy films.
-
D.
Jessica Biel
Jessica Biel is an American actress and producer known for her roles in the TV series "7th Heaven" and films such as "The Texas Chainsaw Massacre" and "The Illusionist."
-
E.
Kate Bosworth
Kate Bosworth is an American actress best known for her roles in films such as "Blue Crush" and "Superman Returns."
- 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_69e24602ae1481908aaa6bc7ca493867 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1907d8be08190a100d99efaff9964 |
completed | April 29, 2026, 5 a.m. |
Created at: April 17, 2026, 4:07 p.m.