Triple

T2700921
Position Surface form Disambiguated ID Type / Status
Subject The Hip-Hop Violinist E59225 entity
Predicate artist P184 FINISHED
Object Miri Ben-Ari E8563 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: Miri Ben-Ari | Statement: [The Hip-Hop Violinist, artist, Miri Ben-Ari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miri Ben-Ari
Context triple: [The Hip-Hop Violinist, artist, Miri Ben-Ari]
  • A. Miri Ben-Ari chosen
    Miri Ben-Ari is an Israeli-American violinist, producer, and composer known for blending classical violin with hip-hop and R&B, collaborating with major artists across genres.
  • B. Moni Naor
    Moni Naor is an Israeli computer scientist renowned for his foundational contributions to cryptography and theoretical computer science.
  • C. Orna Kupferman
    Orna Kupferman is an Israeli computer scientist known for her contributions to formal verification, automata theory, and logic in computer science.
  • D. Oded Maler
    Oded Maler is a computer scientist known for his contributions to formal verification, hybrid systems, and real-time systems theory.
  • E. Orna Grumberg
    Orna Grumberg is a prominent computer scientist known for her contributions to formal verification and model checking.
  • 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_69ab4ac66bc88190b9e4afa5fc843f72 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda4c8d34819094f5e4cbc5a4bb9b completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf7446f08190b5e073278725d1f4 completed March 10, 2026, 5:43 a.m.
Created at: March 6, 2026, 9:55 p.m.