Triple
T13511015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julian Sands |
E321138
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Julian Sands |
E321138
|
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: Julian Sands | Statement: [Julian Sands, name, Julian Sands]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julian Sands Context triple: [Julian Sands, name, Julian Sands]
-
A.
Julian Sands
chosen
Julian Sands was an English actor known for his distinctive presence in films such as "A Room with a View," "Warlock," and "The Killing Fields."
-
B.
Christopher Atkins
Christopher Atkins is an American actor best known for his breakout role in the 1980 film "The Blue Lagoon."
-
C.
Dorian Harewood
Dorian Harewood is an American actor known for his work in film, television, and voice acting, including roles in projects such as Full Metal Jacket and the animated series Batman.
-
D.
Martin Clunes
Martin Clunes is an English actor and comedian best known for his lead role in the television series "Doc Martin" and his work on the sitcom "Men Behaving Badly."
-
E.
Michael York
Michael York is an English actor known for his roles in films such as "Cabaret," "Logan's Run," and the "Austin Powers" series.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf86a6208190be8c18f7a0158f23 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d3afa0c81908733f3fd193d4e0f |
completed | May 3, 2026, 7:08 p.m. |
Created at: April 9, 2026, 9:43 p.m.