Triple
T2831712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rambo III |
E62251
|
entity |
| Predicate | cinematography |
P1953
|
FINISHED |
| Object |
John Stanier
John Stanier is a cinematographer best known for his work on major action films such as "Rambo III."
|
E303382
|
NE FINISHED |
How this triple was built (4 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: John Stanier | Statement: [Rambo III, cinematography, John Stanier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Stanier Context triple: [Rambo III, cinematography, John Stanier]
-
A.
Curtis Stigers
Curtis Stigers is an American jazz and soul-influenced singer, saxophonist, and songwriter known for his early 1990s pop hits and later critically acclaimed jazz recordings.
-
B.
Steve Stiles
Steve Stiles was an American cartoonist and illustrator best known for his influential work in science fiction fandom and fanzines.
-
C.
Matt Messina
Matt Messina is an American film and television composer best known for his award-winning score for the movie "Juno."
-
D.
John Stanly
John Stanly was an American Federalist politician and lawyer from North Carolina who served multiple terms in the U.S. House of Representatives in the early 19th century.
-
E.
Deryck Guyler
Deryck Guyler was a British character actor and comedian best known for his roles in mid-20th-century radio and television sitcoms.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: John Stanier Triple: [Rambo III, cinematography, John Stanier]
Generated description
John Stanier is a cinematographer best known for his work on major action films such as "Rambo III."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Stanier Target entity description: John Stanier is a cinematographer best known for his work on major action films such as "Rambo III."
-
A.
Curtis Stigers
Curtis Stigers is an American jazz and soul-influenced singer, saxophonist, and songwriter known for his early 1990s pop hits and later critically acclaimed jazz recordings.
-
B.
Steve Stiles
Steve Stiles was an American cartoonist and illustrator best known for his influential work in science fiction fandom and fanzines.
-
C.
Matt Messina
Matt Messina is an American film and television composer best known for his award-winning score for the movie "Juno."
-
D.
John Stanly
John Stanly was an American Federalist politician and lawyer from North Carolina who served multiple terms in the U.S. House of Representatives in the early 19th century.
-
E.
Deryck Guyler
Deryck Guyler was a British character actor and comedian best known for his roles in mid-20th-century radio and television sitcoms.
- F. None of above. chosen
Provenance (5 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebe95188190bf65fb4cd88e2ec5 |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8bb92b08190b1de7e6973d96301 |
completed | March 10, 2026, 9:47 a.m. |
| NEDg | Description generation | batch_69afea972cc8819087455f3233f84d21 |
completed | March 10, 2026, 9:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b003cb1b2081909ddf2e6bae3e5491 |
completed | March 10, 2026, 11:43 a.m. |
Created at: March 6, 2026, 10:01 p.m.