Triple
T20488547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gina Kaus |
E502676
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Gina Kaus Wiener |
—
|
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: Gina Kaus Wiener | Statement: [Gina Kaus, alsoKnownAs, Gina Kaus Wiener]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gina Kaus Wiener Context triple: [Gina Kaus, alsoKnownAs, Gina Kaus Wiener]
-
A.
Gina Kaus
chosen
Gina Kaus was an Austrian-American novelist and screenwriter known for her work in mid-20th-century Hollywood cinema.
-
B.
Gina Cass-Gottlieb
Gina Cass-Gottlieb is an Australian lawyer and regulator who serves as the chair of the Australian Competition and Consumer Commission, overseeing competition and consumer protection enforcement.
-
C.
Kim Kashkashian
Kim Kashkashian is an acclaimed American violist renowned for her expressive performances and influential recordings of contemporary and classical repertoire.
-
D.
Geneva Dowd
Geneva Dowd was the wife of American singer and talk show host Mike Douglas.
-
E.
Diane Kagan
Diane Kagan is an American actress known for her supporting role in the 1990 drama film "Mr. and Mrs. Bridge."
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b5c6f84819087d813be3542ed33 |
completed | April 20, 2026, 9:32 p.m. |
Created at: April 16, 2026, 11:34 a.m.