Triple
T17944759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen Moyer |
E448674
|
entity |
| Predicate | coStar |
P43875
|
FINISHED |
| Object | Anna Paquin |
—
|
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: Anna Paquin | Statement: [Stephen Moyer, coStar, Anna Paquin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Paquin Context triple: [Stephen Moyer, coStar, Anna Paquin]
-
A.
Anna Paquin
chosen
Anna Paquin is an Academy Award–winning Canadian-born New Zealand actress known for films such as "The Piano," the "X-Men" series, and the TV series "True Blood."
-
B.
Jessica Paré
Jessica Paré is a Canadian actress best known for her role as Megan Draper on the television series "Mad Men."
-
C.
Danielle Nicolet
Danielle Nicolet is an American actress best known for her role as Cecile Horton on the superhero television series "The Flash."
-
D.
Juliette Lewis
Juliette Lewis is an American actress and singer known for her intense, offbeat performances in films such as "Cape Fear," "Natural Born Killers," and numerous independent productions.
-
E.
Mädchen Amick
Mädchen Amick is an American actress best known for her role as Shelly Johnson in David Lynch’s cult television series Twin Peaks and its later revival.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad9819a88190ad4ea7d562cf3f28 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 10:21 a.m.