Triple
T2900978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greyhound |
E62651
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Stephen Graham |
E117148
|
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: Stephen Graham | Statement: [Greyhound, starring, Stephen Graham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen Graham Context triple: [Greyhound, starring, Stephen Graham]
-
A.
Stephen Graham
chosen
Stephen Graham is an English character actor known for his intense, often gritty performances in films and television series such as "This Is England," "Boardwalk Empire," and "The Irishman."
-
B.
Richard Gant
Richard Gant is an American character actor known for his roles in film and television, often portraying authoritative or tough-minded figures.
-
C.
Robert Watts
Robert Watts is a British film producer best known for his work on major films such as Who Framed Roger Rabbit and entries in the Star Wars and Indiana Jones franchises.
-
D.
Bob Gunton
Bob Gunton is an American character actor best known for his portrayal of the strict prison warden Samuel Norton in the film "The Shawshank Redemption."
-
E.
Martin Henderson
Martin Henderson is a New Zealand actor known for his roles in films like "The Ring" and "Everest" and TV series such as "Grey's Anatomy" and "Virgin River."
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0b261c081909b66b21520b4731b |
completed | March 7, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e1250348190abeac8ef6dd9d916 |
completed | March 11, 2026, 8:55 a.m. |
Created at: March 6, 2026, 10:10 p.m.