Triple
T20552778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jay Adler |
E504638
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Sara Adler |
—
|
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: Sara Adler | Statement: [Jay Adler, mother, Sara Adler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sara Adler Context triple: [Jay Adler, mother, Sara Adler]
-
A.
Sara Adler
chosen
Sara Adler was a prominent Yiddish theater actress and influential figure in early 20th-century American Jewish stage culture.
-
B.
Sarah Adler
Sarah Adler is an Israeli actress known for her work in international arthouse cinema, including acclaimed films by directors such as Amos Gitai and Jean-Luc Godard.
-
C.
Sonia Adler
Sonia Adler is best known as the wife of American novelist and playwright Warren Adler.
-
D.
Sara Kestelman
Sara Kestelman is a British actress known for her work in film, television, and theatre, including a notable role in the 1974 science fiction film "Zardoz."
-
E.
Mary Adler
Mary Adler is the young mathematically gifted girl portrayed by Mckenna Grace in the film "Gifted," around whom the story’s family and ethical dilemmas revolve.
- 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_69e0b4b52c048190952b4d0f430813a3 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5db052c8190801e53f6148113c8 |
completed | April 20, 2026, 10:16 p.m. |
Created at: April 16, 2026, 11:38 a.m.