Triple
T4759811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modern Hebrew literature |
E105672
|
entity |
| Predicate | hasNotableAuthor |
P4244
|
FINISHED |
| Object | Leah Goldberg |
E470953
|
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: Leah Goldberg | Statement: [Modern Hebrew literature, hasNotableAuthor, Leah Goldberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leah Goldberg Context triple: [Modern Hebrew literature, hasNotableAuthor, Leah Goldberg]
-
A.
Leah Goldberg
chosen
Leah Goldberg was a prominent Israeli poet, author, translator, and literary scholar, regarded as one of the central figures of modern Hebrew literature.
-
B.
Myla Goldberg
Myla Goldberg is an American novelist best known for her critically acclaimed debut "Bee Season," which explores family, faith, and identity.
-
C.
Nina Loeb
Nina Loeb was an American socialite and member of the prominent Loeb banking family who married financier and Federal Reserve pioneer Paul Warburg.
-
D.
Lily Schechner
Lily Schechner is the teenage protagonist and aspiring witch at the center of the supernatural coming-of-age story in the film "The Craft: Legacy."
-
E.
Ayelet Zurer
Ayelet Zurer is an Israeli actress known internationally for her roles in films such as "Angels & Demons," "Munich," and "Man of Steel."
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650dc7fc81909b483ef3c456ae0d |
completed | March 20, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5c938c5881908393cf7da23bbc86 |
completed | March 21, 2026, 8:53 a.m. |
Created at: March 20, 2026, 1:20 p.m.