Triple
T15526498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ariel Porat |
E369096
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ariel Porat |
E369096
|
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: Ariel Porat | Statement: [Ariel Porat, name, Ariel Porat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ariel Porat Context triple: [Ariel Porat, name, Ariel Porat]
-
A.
Ariel Porat
chosen
Ariel Porat is an Israeli legal scholar and academic leader who serves as president of Tel Aviv University.
-
B.
Sara Ben-Artzi
Sara Ben-Artzi is an Israeli educational psychologist and public figure best known as the wife of longtime Israeli Prime Minister Benjamin Netanyahu.
-
C.
Nina Katzir
Nina Katzir was the wife of Israeli President Ephraim Katzir and served as Israel’s First Lady in the 1970s, known for her public and social activities.
-
D.
Yoni Brenner
Yoni Brenner is a screenwriter and humorist known for his work on animated films, including contributing to the screenplay of "Rio 2."
-
E.
Nili Priel
Nili Priel is an Israeli public figure best known as the wife of former Prime Minister and Defense Minister Ehud Barak.
- 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_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e04145178481909fb0339a79d4239e |
completed | April 16, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d598e6c8190870e9249197f5f53 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:05 a.m.