Triple
T22594076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Cleveland |
E574625
|
entity |
| Predicate | notableCollaboration |
P8554
|
FINISHED |
| Object | Grant Thompson |
—
|
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: Grant Thompson | Statement: [Christopher Cleveland, notableCollaboration, Grant Thompson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grant Thompson Context triple: [Christopher Cleveland, notableCollaboration, Grant Thompson]
-
A.
Grant Thompson
chosen
Grant Thompson is a screenwriter best known for his work on the inspirational sports drama film "McFarland, USA."
-
B.
Patrick Rothfuss
Patrick Rothfuss is an American fantasy author best known for his acclaimed series "The Kingkiller Chronicle," beginning with "The Name of the Wind."
-
C.
Brent Weeks
Brent Weeks is an American fantasy author best known for his popular series such as *The Night Angel Trilogy* and *Lightbringer*.
-
D.
Joe Abercrombie
Joe Abercrombie is a British fantasy author best known for his gritty, darkly humorous First Law series, which helped popularize the grimdark subgenre.
-
E.
Rob Hawkins
Rob Hawkins is the main protagonist and camcorder-wielding narrator in the 2008 found-footage monster film "Cloverfield."
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f16164d690819096f7c4efb6cedad9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 2:49 p.m.