Triple
T11377173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larry Riley |
E269499
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Larry Riley |
E269499
|
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: Larry Riley | Statement: [Larry Riley, name, Larry Riley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larry Riley Context triple: [Larry Riley, name, Larry Riley]
-
A.
Larry Riley
chosen
Larry Riley was an American actor best known for his roles in film, television, and theater, including a prominent performance in the drama "A Soldier's Story."
-
B.
John Briley
John Briley was an American screenwriter best known for his Academy Award-winning work on the film "Gandhi" and other politically charged dramas.
-
C.
Lawrence Riley
Lawrence Riley was an American playwright and screenwriter best known for his work on mid-20th-century stage and film comedies.
-
D.
Jeff Cunningham
Jeff Cunningham is a former professional soccer forward best known as one of Major League Soccer’s most prolific goal scorers.
-
E.
Bill Yates
Bill Yates is a computer engineer best known for his role in developing the pioneering MITS Altair 8800 microcomputer, which helped spark the personal computing revolution in the mid-1970s.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea8e6d44819095f949581421e98e |
completed | April 9, 2026, 6:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58bff6574819089bd63266b97a734 |
completed | April 20, 2026, 2:14 a.m. |
Created at: April 8, 2026, 9:33 p.m.