Triple
T9958173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moni Naor |
E195495
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object | Yuval Ishai |
E413703
|
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: Yuval Ishai | Statement: [Moni Naor, notableStudent, Yuval Ishai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuval Ishai Context triple: [Moni Naor, notableStudent, Yuval Ishai]
-
A.
Yuval Ishai
chosen
Yuval Ishai is a computer scientist known for his influential work in cryptography, particularly in secure multiparty computation and related areas of theoretical cryptography.
-
B.
Yair Shamir
Yair Shamir is an Israeli businessman, former military officer, and politician who served as a government minister and is the son of former Prime Minister Yitzhak Shamir.
-
C.
Iftach Haitner
Iftach Haitner is an Israeli computer scientist and cryptographer known for his contributions to the foundations of cryptography and computational complexity.
-
D.
Moni Naor
Moni Naor is an Israeli computer scientist renowned for his foundational contributions to cryptography and theoretical computer science.
-
E.
Tsachy Weissman
Tsachy Weissman is an information theorist and electrical engineer known for his contributions to data compression, signal processing, and information theory, and as a professor at Stanford University.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb6cec7dc8190bb7e43c82a317707 |
completed | April 2, 2026, 12:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257aa73d4819081f77f8386449905 |
completed | April 5, 2026, 12:38 p.m. |
Created at: March 30, 2026, 8:46 p.m.