Triple
T22840583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unbelievable |
E566067
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Ayelet Waldman |
—
|
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: Ayelet Waldman | Statement: [Unbelievable, createdBy, Ayelet Waldman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayelet Waldman Context triple: [Unbelievable, createdBy, Ayelet Waldman]
-
A.
Ayelet Waldman
chosen
Ayelet Waldman is an Israeli-American novelist, essayist, and former public defender known for her candid, often controversial writing on motherhood, marriage, and mental health.
-
B.
Eyal Waldman
Eyal Waldman is an Israeli entrepreneur and engineer best known as the co-founder and longtime CEO of high-performance networking company Mellanox Technologies.
-
C.
Laura Shusterman
Laura Shusterman is the wife of former Donald Trump attorney Michael Cohen and a Ukrainian-born businesswoman who has been linked to some of his real estate and taxi-medallion ventures.
-
D.
Lisa Davidowitz
Lisa Davidowitz is a screenwriter best known for her work on the film "Uptown Girls."
-
E.
Emily Frankel
Emily Frankel is an American dancer, choreographer, and writer known for her work in modern dance and for her long career in the performing arts.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e83fa48819084568264ef45c833 |
completed | April 29, 2026, 3:44 a.m. |
Created at: April 17, 2026, 3:35 p.m.