Triple
T21341382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Kicks" |
E526199
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Chris Donlon |
—
|
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 Donlon | Statement: ["Kicks", editor, Chris Donlon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Donlon Context triple: ["Kicks", editor, Chris Donlon]
-
A.
Chris Donlon
chosen
Chris Donlon is a film editor known for his work on the feature film "Kicks."
-
B.
Ian Donnelly
Ian Donnelly is a theoretical physicist and linguist who serves as one of the central human protagonists in the science fiction film "Arrival," working alongside Louise Banks to communicate with extraterrestrial visitors.
-
C.
Keith Donnellan
Keith Donnellan was an American philosopher best known for his influential work in the philosophy of language, especially on reference, definite descriptions, and the distinction between referential and attributive uses.
-
D.
Sam Donnelly
Sam Donnelly is a television producer best known for serving as an executive producer on the popular talent competition show "America's Got Talent."
-
E.
Tom Doherty
Tom Doherty is an American publisher best known as the founder of the science fiction and fantasy imprint Tor Books.
- 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_69e0b51c33048190ab27cede74ef798c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5ba7ce3c8190ba5ded980a9866f2 |
completed | April 26, 2026, 6:38 p.m. |
Created at: April 16, 2026, 4:44 p.m.