Triple
T10855953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvia Miles |
E256269
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sylvia Miles |
E256269
|
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: Sylvia Miles | Statement: [Sylvia Miles, name, Sylvia Miles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylvia Miles Context triple: [Sylvia Miles, name, Sylvia Miles]
-
A.
Sylvia Miles
chosen
Sylvia Miles was an American actress best known for her Oscar-nominated supporting role as a jaded New York socialite in the film "Midnight Cowboy."
-
B.
Amy Rydell
Amy Rydell is an actress known for her role in the 2001 biographical television film "James Dean."
-
C.
Diane Ayres
Diane Ayres is an American writer and editor known for her work in fiction and essays, often exploring contemporary relationships and women's experiences.
-
D.
Frances Charles
Frances Charles was the wife of American film actor Victor Mature, known primarily for her marriage to the Hollywood star.
-
E.
Marilyn Vance
Marilyn Vance is an American costume designer known for her influential work on numerous popular films, including iconic 1980s and 1990s movies.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75135df24819090ce43afa3ea9b38 |
completed | April 9, 2026, 7:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a91a3e1c819083ef144e7fd5603f |
completed | April 18, 2026, 3:54 p.m. |
Created at: April 8, 2026, 9:20 p.m.