Triple
T21536911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Misconduct |
E531371
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Chris Marquette |
—
|
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: Chris Marquette | Statement: [Misconduct, hasCastMember, Chris Marquette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Marquette Context triple: [Misconduct, hasCastMember, Chris Marquette]
-
A.
Chris Marquette
chosen
Chris Marquette is an American actor known for his roles in horror and comedy films as well as television series such as "Joan of Arcadia."
-
B.
Nick Marone
Nick Marone is a fictional character from the soap opera "The Bold and the Beautiful," known for his complex romantic entanglements and family drama.
-
C.
Mike Guardia
Mike Guardia is a military historian and author known for writing detailed biographies and accounts of notable U.S. Army commanders and combat operations.
-
D.
Joe Maross
Joe Maross was an American character actor known for his numerous film and television roles from the 1950s through the 1980s, including appearances in classic series like "The Twilight Zone."
-
E.
Jayson Crothers
Jayson Crothers is a cinematographer known for his work on independent films and television series, including the feature film "She Wants Me."
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0e5a9c8190894ec3666d3296aa |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.