Triple
T15368312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catch .44 |
E367472
|
entity |
| Predicate | cinematography |
P1953
|
FINISHED |
| Object |
James Liston
James Liston is a cinematographer known for his work on the crime thriller film "Catch .44."
|
E1152826
|
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: James Liston | Statement: [Catch .44, cinematography, James Liston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Liston Context triple: [Catch .44, cinematography, James Liston]
-
A.
Thomas Denman
Thomas Denman was a prominent 19th-century English lawyer and politician who later became Lord Chief Justice of England and Wales.
-
B.
John Gillies
John Gillies is a name shared by several notable individuals, including historians, politicians, and public figures from English-speaking countries.
-
C.
Tom Bancroft
Tom Bancroft is an American animator, illustrator, and character designer best known for his work on Disney films such as "Mulan" and "The Lion King."
-
D.
Thomas Bragg
Thomas Bragg was an American politician and lawyer who served as a U.S. senator and governor of North Carolina before becoming attorney general of the Confederate States during the Civil War.
-
E.
John Bragg
John Bragg was a prominent 19th-century figure from Mobile, Alabama, for whom the historic Bragg-Mitchell Mansion is named.
- 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: James Liston Triple: [Catch .44, cinematography, James Liston]
Generated description
James Liston is a cinematographer known for his work on the crime thriller film "Catch .44."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: James Liston Target entity description: James Liston is a cinematographer known for his work on the crime thriller film "Catch .44."
-
A.
Thomas Denman
Thomas Denman was a prominent 19th-century English lawyer and politician who later became Lord Chief Justice of England and Wales.
-
B.
John Gillies
John Gillies is a name shared by several notable individuals, including historians, politicians, and public figures from English-speaking countries.
-
C.
Tom Bancroft
Tom Bancroft is an American animator, illustrator, and character designer best known for his work on Disney films such as "Mulan" and "The Lion King."
-
D.
Thomas Bragg
Thomas Bragg was an American politician and lawyer who served as a U.S. senator and governor of North Carolina before becoming attorney general of the Confederate States during the Civil War.
-
E.
John Bragg
John Bragg was a prominent 19th-century figure from Mobile, Alabama, for whom the historic Bragg-Mitchell Mansion is named.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4a7cdc8190b7b48c97e774c306 |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b50703881909ca71c985bc1c7b5 |
completed | May 9, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69ff0cb1b9188190b0eb99661d26206f |
completed | May 9, 2026, 10:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff0d3182f08190abd463d921e1830e |
completed | May 9, 2026, 10:32 a.m. |
Created at: April 10, 2026, 3:18 a.m.