Triple
T18463962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pirates of Silicon Valley |
E451109
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Martyn Burke |
—
|
NE NERFINISHED |
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: Martyn Burke | Statement: [Pirates of Silicon Valley, writer, Martyn Burke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martyn Burke Context triple: [Pirates of Silicon Valley, writer, Martyn Burke]
-
A.
Martyn Burke
chosen
Martyn Burke is a Canadian filmmaker and writer known for his work as a screenwriter and director in both film and television, often blending satire with political and social themes.
-
B.
Martyn Eaden
Martyn Eaden is a British screenwriter best known for his past marriage to American actress Chrissy Metz.
-
C.
Michael Hoskin
Michael Hoskin is a British historian of astronomy known for his influential scholarship on the history of astronomical thought and institutions.
-
D.
Ken Burridge
Ken Burridge is a journalist and commentator known for his work covering environmental issues, finance, and cryptocurrency.
-
E.
Graham Martin
Graham Martin was an American diplomat best known for serving as the last U.S. ambassador to South Vietnam during the final years of the Vietnam War.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52a8190508190a74b1d3482364905 |
completed | April 19, 2026, 7:18 p.m. |
Created at: April 10, 2026, 11:33 a.m.