Triple
T18731416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Mississippi |
E458042
|
entity |
| Predicate | alsoStarring |
P14987
|
FINISHED |
| Object | Rya Kihlstedt |
—
|
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: Rya Kihlstedt | Statement: [One Mississippi, alsoStarring, Rya Kihlstedt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rya Kihlstedt Context triple: [One Mississippi, alsoStarring, Rya Kihlstedt]
-
A.
Rya Kihlstedt
chosen
Rya Kihlstedt is an American actress known for her work in film and television, including prominent roles in series such as "A Teacher."
-
B.
Kelli Rhoads
Kelli Rhoads is a musician best known for her association with the American glam metal band Ratt.
-
C.
Kirsten Vangsness
Kirsten Vangsness is an American actress best known for her role as technical analyst Penelope Garcia on the television series "Criminal Minds."
-
D.
Kellie Carlson
Kellie Carlson is an actress known for playing the character Wilma Deering in an adaptation of the Buck Rogers science fiction franchise.
-
E.
Kelli Stavast
Kelli Stavast is an American sports broadcaster best known for her work as a pit reporter and analyst on NBC’s NASCAR coverage.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d7854748190b66c4aaadfd67f29 |
completed | April 20, 2026, 12:04 a.m. |
Created at: April 10, 2026, 11:51 a.m.