Triple
T19289296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grace Van Dien |
E482397
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Grace Van Dien |
—
|
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: Grace Van Dien | Statement: [Grace Van Dien, name, Grace Van Dien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grace Van Dien Context triple: [Grace Van Dien, name, Grace Van Dien]
-
A.
Grace Van Dien
chosen
Grace Van Dien is an American actress and streamer known for roles in projects like "Stranger Things" and "The Village."
-
B.
Amy Landecker
Amy Landecker is an American actress best known for her role as Sarah Pfefferman on the television series "Transparent."
-
C.
Carol Diener
Carol Diener is an American psychologist known for her work in collaboration with her late husband, well-being researcher Ed Diener, particularly in the field of subjective well-being and happiness.
-
D.
Darlanne Fluegel
Darlanne Fluegel was an American actress and model known for her roles in 1980s films and television, including prominent appearances in crime and action genres.
-
E.
Cynthia Ludwig
Cynthia Ludwig is a film editor known for her work on the 2009 horror film "My Bloody Valentine 3D."
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc050a888190ac204d1e736200c5 |
completed | April 20, 2026, 10:12 a.m. |
Created at: April 10, 2026, 1:30 p.m.