Triple

T9961814
Position Surface form Disambiguated ID Type / Status
Subject Hugo Krawczyk E195586 entity
Predicate hasAcademicAdvisor P167 FINISHED
Object Shmuel Winograd E707714 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: Shmuel Winograd | Statement: [Hugo Krawczyk, hasAcademicAdvisor, Shmuel Winograd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shmuel Winograd
Context triple: [Hugo Krawczyk, hasAcademicAdvisor, Shmuel Winograd]
  • A. Shmuel Winograd chosen
    Shmuel Winograd was a prominent computer scientist known for his influential work in computational complexity and fast algorithms, particularly in matrix multiplication.
  • B. Moshe Rosenblum
    Moshe Rosenblum is known primarily as the son of Herzl Rosenblum, a prominent Israeli journalist, politician, and signatory of the Israeli Declaration of Independence.
  • C. Shimon Even
    Shimon Even was an influential Israeli computer scientist known for his foundational contributions to graph algorithms and computational complexity theory.
  • D. Shmuel Shtrikman
    Shmuel Shtrikman was an Israeli physicist renowned for his influential contributions to condensed matter physics and materials science.
  • E. Daniel G. Bobrow
    Daniel G. Bobrow was an influential American computer scientist and early artificial intelligence researcher known for his work on natural language understanding and AI programming systems.
  • 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_69ca82ebd1288190912f9e4482d1fa35 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb6d37f0c8190946b958c399f3250 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, 8:47 p.m.