Triple
T20674699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvia Hoeks |
E508128
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sylvia |
—
|
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: Sylvia | Statement: [Sylvia Hoeks, givenName, Sylvia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylvia Context triple: [Sylvia Hoeks, givenName, Sylvia]
-
A.
Sylvia
Sylvia is a key character in the film "The Truman Show," a woman who tries to reveal the truth to Truman about his manufactured reality and becomes his inspiration to escape.
-
B.
Sylvia
"Sylvia" is a stage play best known from its Broadway revival starring Annaleigh Ashford as a dog who upends her owners’ lives with her exuberant personality.
-
C.
Sylvia
chosen
Sylvia is a feminine given name of Latin origin meaning "from the forest" or "of the woods."
-
D.
Sylvia
Sylvia is a central female character in George Farquhar’s Restoration comedy "The Recruiting Officer," known for her wit, disguise, and critique of gender and social norms.
-
E.
Sylvia
Sylvia is a character in the film "Birdman," known as the ex-wife of the troubled actor Riggan Thomson.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5cdbec48190a945261c41d810ce |
completed | April 20, 2026, 11:25 p.m. |
Created at: April 16, 2026, 11:44 a.m.