Triple
T18058199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbet Palme |
E432096
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lisbeth |
—
|
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: Lisbeth | Statement: [Lisbet Palme, givenName, Lisbeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisbeth Context triple: [Lisbet Palme, givenName, Lisbeth]
-
A.
Lisbeth
chosen
Lisbeth is a feminine given name, typically used as a shortened or variant form of Elizabeth.
-
B.
Lisbeth Fischer
Lisbeth Fischer is a central character in Honoré de Balzac’s novel "Cousin Bette," known for her vengeful scheming against her more prosperous relatives in Parisian high society.
-
C.
Lisbeth Salander
Lisbeth Salander is a brilliant but troubled hacker and investigator at the center of Stieg Larsson’s Millennium crime novels, known for her fierce independence, photographic memory, and uncompromising sense of justice.
-
D.
Lisbeth Hummel
Lisbeth Hummel is a film producer best known for her work on major Hollywood thrillers such as "The Sum of All Fears."
-
E.
Elizabeth Karlsen
Elizabeth Karlsen is a British film producer known for acclaimed independent films such as "Carol," "Made in Dagenham," and "Little Voice," and as co-founder of the production company Number 9 Films.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c1048c00819097c7dfbf76bb0987 |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 10:26 a.m.