Triple

T20836622
Position Surface form Disambiguated ID Type / Status
Subject Miklós Ajtai E512974 entity
Predicate coAuthor P398 FINISHED
Object Noga Alon NE NERFINISHED

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: [Miklós Ajtai, coAuthor, Noga Alon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noga Alon
Context triple: [Miklós Ajtai, coAuthor, 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. Assaf Naor
    Assaf Naor is an Israeli mathematician renowned for his work in functional analysis, metric geometry, and theoretical computer science.
  • C. Eli Upfal
    Eli Upfal is a computer scientist known for his contributions to randomized algorithms, probabilistic analysis, and theoretical computer science.
  • D. Eyal Kushilevitz
    Eyal Kushilevitz is an Israeli computer scientist known for his influential work in cryptography, communication complexity, and theoretical computer science.
  • E. Moni Naor
    Moni Naor is an Israeli computer scientist renowned for his foundational contributions to cryptography and theoretical computer science.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c326daec8190bd4caa41a4b38833 completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:42 p.m.