Triple
T17746412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Cox |
E443001
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Charlie Thomas Cox |
—
|
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: Charlie Thomas Cox | Statement: [Charlie Cox, birthName, Charlie Thomas Cox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charlie Thomas Cox Context triple: [Charlie Cox, birthName, Charlie Thomas Cox]
-
A.
Charlie Cox
chosen
Charlie Cox is a British actor best known for portraying Matt Murdock/Daredevil in the Marvel television series "Daredevil" and related Marvel Cinematic Universe projects.
-
B.
James Whishaw
James Whishaw is the twin brother of English actor Ben Whishaw.
-
C.
Charlie Heaton
Charlie Heaton is an English actor best known for playing Jonathan Byers in the hit Netflix sci-fi horror series "Stranger Things."
-
D.
Bob Morley
Bob Morley is an Australian actor best known for playing Bellamy Blake on the post-apocalyptic television series "The 100."
-
E.
Dominic Cooper
Dominic Cooper is an English actor known for his roles in films such as "Mamma Mia!" and "The Devil's Double," as well as the TV series "Preacher."
- 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_69e47ad26940819090696c2cb86fd606 |
completed | April 19, 2026, 6:48 a.m. |
Created at: April 10, 2026, 10:09 a.m.