Triple
T12592087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa |
E300630
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Lisbeth |
E214703
|
NE FINISHED |
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: [Lisa, hasRelatedName, Lisbeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisbeth Context triple: [Lisa, hasRelatedName, Lisbeth]
-
A.
Lisbeth
chosen
Lisbeth is a feminine given name, typically used as a shortened or variant form of Elizabeth.
-
B.
Lisbeth Hummel
Lisbeth Hummel is a film producer best known for her work on major Hollywood thrillers such as "The Sum of All Fears."
-
C.
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.
-
D.
Sarah Lund
Sarah Lund is a meticulous and emotionally reserved Copenhagen detective renowned for her relentless pursuit of complex murder cases in the Danish crime series "The Killing."
-
E.
Karla
Karla is the elusive Soviet spymaster and primary antagonist of John le Carré’s George Smiley novels, symbolizing the Cold War espionage rivalry between British intelligence and the KGB.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cc6d3c81908fbb22601c46f3f7 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ec2dac88190bf31bb00f93feb30 |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 9, 2026, 5:07 p.m.