Triple
T10201969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red 2 |
E238903
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Brian Cox |
E70759
|
NE FINISHED |
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: Brian Cox | Statement: [Red 2, hasCastMember, Brian Cox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Cox Context triple: [Red 2, hasCastMember, Brian Cox]
-
A.
Brian Cox
chosen
Brian Cox is a Scottish actor known for his powerful performances in film, television, and theater, including roles in movies like "The Long Kiss Goodnight" and the TV series "Succession."
-
B.
Brian Cox
Brian Cox is a British physicist and popular science communicator known for presenting BBC science programs and making complex physics accessible to the public.
-
C.
Brian Michael Cox
Brian Michael Cox is a Grammy-winning American songwriter and record producer known for his work on numerous R&B and pop hits.
-
D.
George Norton
George Norton was a British colonial-era lawyer and educator best known for establishing Presidency College in Madras, one of India’s earliest and most prestigious institutions of higher learning.
-
E.
Bruce Greenwood
Bruce Greenwood is a Canadian actor known for his versatile roles in film and television, including prominent performances in projects like "Star Trek," "Thirteen Days," and numerous acclaimed dramas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca84e1ea088190b38162e43d4cfa8f |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdee40cb7481908a1bf4d5636eb8ef |
completed | April 2, 2026, 4:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d32afa75ec8190bbaf2e69b4ee24f1 |
completed | April 6, 2026, 3:39 a.m. |
Created at: March 30, 2026, 9:14 p.m.