Triple
T22093641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AVP: Requiem |
E545968
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Reiko Aylesworth |
—
|
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: Reiko Aylesworth | Statement: [AVP: Requiem, stars, Reiko Aylesworth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reiko Aylesworth Context triple: [AVP: Requiem, stars, Reiko Aylesworth]
-
A.
Reiko Aylesworth
chosen
Reiko Aylesworth is an American actress best known for her role as Michelle Dessler on the television series "24."
-
B.
Keiko O'Brien
Keiko O'Brien is a civilian botanist and schoolteacher in the Star Trek universe, best known for her appearances on Star Trek: The Next Generation and Deep Space Nine.
-
C.
Yukiko Hoffman
Yukiko Hoffman is a member of the organization or group known as Mobius.
-
D.
Eleanor Matsuura
Eleanor Matsuura is a British actress known for her work in television, film, and theatre, including prominent roles in series such as The Walking Dead and Sherlock.
-
E.
Rachel Ichikawa Scott
Rachel Ichikawa Scott is best known as the wife of former NFL wide receiver and Pac-12 Conference commissioner Larry Scott.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e766388190aad1039fe0849771 |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.