Triple
T17676872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Prince |
E440663
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Matthew Prince |
—
|
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: Matthew Prince | Statement: [Matthew Prince, name, Matthew Prince]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Prince Context triple: [Matthew Prince, name, Matthew Prince]
-
A.
Matthew Prince
chosen
Matthew Prince is an American technology entrepreneur best known as the co-founder and CEO of the internet security and performance company Cloudflare.
-
B.
Daniel Grayson
Daniel Grayson is a central character in the TV drama "Revenge," known as the wealthy and conflicted heir of the powerful Grayson family.
-
C.
Peter Prince
Peter Prince is a writer best known for his work on the film "The Hit."
-
D.
Nick Marston
Nick Marston is a television and film producer best known for his executive production work on the adaptation of "Jonathan Strange & Mr Norrell."
-
E.
Owen Harper
Owen Harper is a central character in the British sci-fi series "Torchwood," serving as the team's acerbic and brilliant medical officer.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f6d9ab88190ab0e25eac8b0101c |
completed | April 19, 2026, 6 a.m. |
Created at: April 10, 2026, 10:01 a.m.