Triple

T3143469
Position Surface form Disambiguated ID Type / Status
Subject Jesus Walks E65707 entity
Predicate producer P490 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: [Jesus Walks, producer, Miri Ben-Ari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miri Ben-Ari
Context triple: [Jesus Walks, producer, 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. Rachel Yanait Ben-Zvi
    Rachel Yanait Ben-Zvi was a prominent Zionist activist, educator, and leader in the Jewish labor movement in pre-state Israel, and the wife of Israel’s second president, Yitzhak Ben-Zvi.
  • D. Orna Kupferman
    Orna Kupferman is an Israeli computer scientist known for her contributions to formal verification, automata theory, and logic in computer science.
  • E. Oded Maler
    Oded Maler is a computer scientist known for his contributions to formal verification, hybrid systems, and real-time systems theory.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada59489a88190b0962cef091f4ddb completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224e9029c8190bd88dbb18b5f71a8 completed March 12, 2026, 2:28 a.m.
Created at: March 8, 2026, 3:05 p.m.