Triple
T10194520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moonhaven |
E238125
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Ayelet Zurer |
E89512
|
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: Ayelet Zurer | Statement: [Moonhaven, castMember, Ayelet Zurer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayelet Zurer Context triple: [Moonhaven, castMember, Ayelet Zurer]
-
A.
Ayelet Zurer
chosen
Ayelet Zurer is an Israeli actress known internationally for her roles in films such as "Angels & Demons," "Munich," and "Man of Steel."
-
B.
Yona Wallach
Yona Wallach was an influential Israeli poet known for her experimental, provocative, and psychologically charged Hebrew poetry that challenged social and sexual norms.
-
C.
Daphna Kastner
Daphna Kastner is a Canadian actress, screenwriter, and director known for her work in independent films.
-
D.
Nami Melumad
Nami Melumad is an Israeli-Dutch film and television composer known for her work on major franchises including the Marvel Cinematic Universe and Star Trek.
-
E.
Yoni Brenner
Yoni Brenner is a screenwriter and humorist known for his work on animated films, including contributing to the screenplay of "Rio 2."
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedc7cc748190bceb8f657afcc054 |
completed | April 2, 2026, 4:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d32aef701c8190a01e632eb4fda1b9 |
completed | April 6, 2026, 3:39 a.m. |
Created at: March 30, 2026, 9:13 p.m.