Triple
T18177017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot in Cleveland |
E435188
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Elka Ostrovsky |
—
|
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: Elka Ostrovsky | Statement: [Hot in Cleveland, character, Elka Ostrovsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elka Ostrovsky Context triple: [Hot in Cleveland, character, Elka Ostrovsky]
-
A.
Elka Ostrovsky
chosen
Elka Ostrovsky is a sharp-tongued, eccentric elderly woman and main character on the sitcom "Hot in Cleveland," portrayed by Betty White.
-
B.
Olive Ostrovsky
Olive Ostrovsky is a shy, emotionally neglected young girl and one of the central child contestants in the musical comedy "The 25th Annual Putnam County Spelling Bee."
-
C.
Alisa Freindlich
Alisa Freindlich is a renowned Soviet and Russian actress celebrated for her work in film and theater, particularly in the late 20th century.
-
D.
Anita Goshkin
Anita Goshkin was the first wife of Nobel Prize–winning American novelist Saul Bellow.
-
E.
Lila Kolodny
Lila Kolodny is the bride whose honeymoon quickly unravels in the 1972 romantic comedy film "The Heartbreak Kid."
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df5a72008190bd2e56205b995a87 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 10:31 a.m.