Triple

T17693946
Position Surface form Disambiguated ID Type / Status
Subject Tom Erez E441109 entity
Predicate coAuthorWith P398 FINISHED
Object Yuval Tassa E441110 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 Tassa | Statement: [Tom Erez, coAuthorWith, Yuval Tassa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yuval Tassa
Context triple: [Tom Erez, coAuthorWith, Yuval Tassa]
  • A. Yuval Tassa chosen
    Yuval Tassa is a researcher in reinforcement learning and control who co-authored the work that introduced the Deep Deterministic Policy Gradient (DDPG) algorithm.
  • B. Yuval Ishai
    Yuval Ishai is a computer scientist known for his influential work in cryptography, particularly in secure multiparty computation and related areas of theoretical cryptography.
  • C. Uriel Feige
    Uriel Feige is an Israeli computer scientist known for his influential work in computational complexity theory, approximation algorithms, and probabilistically checkable proofs.
  • D. Gavriel Shamir
    Gavriel Shamir was an Israeli graphic designer best known for co-designing the official emblem of the State of Israel.
  • E. Jonathan Rothberg
    Jonathan Rothberg is an American scientist, inventor, and entrepreneur best known for pioneering next-generation DNA sequencing technologies and founding multiple genomics companies.
  • 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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4715485d88190b9b6f347ff85d7c7 completed April 19, 2026, 6:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02301aab388190a6a44feb57468201 completed May 11, 2026, 7:38 p.m.
Created at: April 10, 2026, 10:04 a.m.