Triple
T15631061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sex/Life |
E375811
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | J. Miles Dale |
E266035
|
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: J. Miles Dale | Statement: [Sex/Life, executiveProducer, J. Miles Dale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: J. Miles Dale Context triple: [Sex/Life, executiveProducer, J. Miles Dale]
-
A.
J. Miles Dale
chosen
J. Miles Dale is a Canadian film and television producer best known for his Academy Award–winning work on Guillermo del Toro's fantasy romance film "The Shape of Water."
-
B.
Dale Van Sickel
Dale Van Sickel was an American actor and pioneering Hollywood stuntman known for his work in numerous action films and serials from the 1930s through the 1950s.
-
C.
Dale Jennings
Dale Jennings is a central fictional television news reporter character in the Australian drama series "The Newsreader."
-
D.
John Diehl
John Diehl is an American character actor best known for his role as Detective Larry Zito on the 1980s television series "Miami Vice."
-
E.
Dale Eunson
Dale Eunson was an American writer and magazine editor best known for his short stories and screenwriting work in mid-20th-century Hollywood.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb536348190b93ed3c178d1ffb8 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c32b4a88190a07db59965b38890 |
completed | May 11, 2026, 7:58 a.m. |
Created at: April 10, 2026, 4:14 a.m.