Triple
T22654658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Backer |
E559192
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Harriet Backer |
—
|
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: Harriet Backer | Statement: [Harriet Backer, fullName, Harriet Backer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harriet Backer Context triple: [Harriet Backer, fullName, Harriet Backer]
-
A.
Harriet Backer
chosen
Harriet Backer was a prominent Norwegian painter known for her richly colored interior scenes and significant contribution to 19th-century Scandinavian art.
-
B.
Louisa Krause
Louisa Krause is an American actress known for her work in independent films and television, including a starring role in the 2018 psychological horror film "Skin."
-
C.
Harriet B. Helberg
Harriet B. Helberg is an American casting director and the mother of actor and comedian Simon Helberg.
-
D.
Harriet Dyer
Harriet Dyer is an Australian actress known for her work in television and film, including prominent roles in series like "Love Child" and the horror-thriller genre.
-
E.
Martha Nielsen
Martha Nielsen is a central character in the German sci-fi thriller series "Dark," whose complex relationships and time-travel entanglements are pivotal to the show's overarching mystery.
- 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765a97ac819095f21ccbdada1d0a |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 3:06 p.m.