Triple
T17746970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hush |
E443012
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Riley Finn |
—
|
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: Riley Finn | Statement: [Hush, mainCharacter, Riley Finn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Riley Finn Context triple: [Hush, mainCharacter, Riley Finn]
-
A.
Riley Finn
chosen
Riley Finn is a character from the television series "Buffy the Vampire Slayer," a soldier in a secret demon-hunting military initiative who becomes one of Buffy Summers' significant romantic partners.
-
B.
Riley Grant
Riley Grant is a fictional character portrayed by Canadian actress Lindy Booth, best known from the Disney Channel series "The Famous Jett Jackson."
-
C.
Riley Shanahan
Riley Shanahan is an American actor and performer best known for physically portraying Robotman in the television series "Doom Patrol."
-
D.
Riley Mackin
Riley Mackin is a songwriter and music professional recognized for his contribution to the Song of the Year–winning work at the 61st Annual Grammy Awards.
-
E.
Riley McCormick
Riley McCormick is an alumnus of University High School in Irvine, California.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47ad33160819093c9bbd3c8957314 |
completed | April 19, 2026, 6:48 a.m. |
Created at: April 10, 2026, 10:09 a.m.