Triple
T16129586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Larkin |
E391358
|
entity |
| Predicate | notableRelative |
P367
|
FINISHED |
| Object | Toby Stephens |
E197280
|
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: Toby Stephens | Statement: [Chris Larkin, notableRelative, Toby Stephens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toby Stephens Context triple: [Chris Larkin, notableRelative, Toby Stephens]
-
A.
Toby Stephens
chosen
Toby Stephens is a British actor known for his versatile film, television, and stage roles, including performances in productions such as the James Bond film "Die Another Day" and the TV series "Black Sails."
-
B.
Toby Rowland
Toby Rowland is a tech entrepreneur best known as a co-founder of the mobile gaming company behind the hit game Candy Crush Saga.
-
C.
Toby Nealey
Toby Nealey is the central protagonist of the British thriller film "I Came By," around whom the story’s suspenseful events and moral conflicts revolve.
-
D.
Toby Parkes
Toby Parkes is an actor known for his role in the British dark comedy film "Keeping Mum."
-
E.
Toby Marks
Toby Marks is an actor known for appearing in the exploitation film "Caged Heat."
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e202075860819088d27d921609a6ce |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7a0ed9c8190a10fa88ee94811cb |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.