Triple

T6258504
Position Surface form Disambiguated ID Type / Status
Subject Shimon Even E140233 entity
Predicate academicAdvisorOf P167 FINISHED
Object Noga Alon E157415 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: Noga Alon | Statement: [Shimon Even, academicAdvisorOf, Noga Alon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noga Alon
Context triple: [Shimon Even, academicAdvisorOf, Noga Alon]
  • A. Noga Alon chosen
    Noga Alon is an Israeli mathematician renowned for his influential work in combinatorics, graph theory, and theoretical computer science.
  • B. Eyal Kushilevitz
    Eyal Kushilevitz is an Israeli computer scientist known for his influential work in cryptography, communication complexity, and theoretical computer science.
  • C. Moni Naor
    Moni Naor is an Israeli computer scientist renowned for his foundational contributions to cryptography and theoretical computer science.
  • D. Ehud Kalai
    Ehud Kalai is an Israeli-American game theorist and economist known for his influential contributions to bargaining theory, game theory, and economic theory.
  • E. Micha Sharir
    Micha Sharir is an Israeli computer scientist and mathematician known for his influential work in computational geometry and discrete mathematics.
  • 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_69c008c95c5c819084bd3dd56133d84d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06367e0b48190967ebfb9bfbc9732 completed March 22, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5192b99d4819083ab6e6f2092547b completed March 26, 2026, 11:31 a.m.
Created at: March 22, 2026, 4:24 p.m.