Triple
T21032757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Dons-Kaufmann |
E518104
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Anna Dons-Kaufmann |
—
|
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: Anna Dons-Kaufmann | Statement: [Anna Dons-Kaufmann, name, Anna Dons-Kaufmann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Dons-Kaufmann Context triple: [Anna Dons-Kaufmann, name, Anna Dons-Kaufmann]
-
A.
Anna Dons-Kaufmann
chosen
Anna Dons-Kaufmann was the wife of physician, social critic, and Zionist leader Max Nordau, known primarily through her association with his life and work.
-
B.
Daphne Kluger
Daphne Kluger is a glamorous, high-profile actress and the unsuspecting target of the jewel heist in the film "Ocean's 8."
-
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.
Elka Ostrovsky
Elka Ostrovsky is a sharp-tongued, eccentric elderly woman and main character on the sitcom "Hot in Cleveland," portrayed by Betty White.
-
E.
Eleanor Sokoloff
Eleanor Sokoloff was a renowned American pianist and long-serving pedagogue celebrated for training generations of leading pianists at the Curtis Institute of Music.
- 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_69e0b503275c8190afd9a163f997c709 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc83828c81909c1ec745c0313c9f |
completed | April 21, 2026, 4:26 a.m. |
Created at: April 16, 2026, 1:56 p.m.