Triple

T12234619
Position Surface form Disambiguated ID Type / Status
Subject Teo Macero E291558 entity
Predicate collaboratedWith P435 FINISHED
Object Tony Bennett E60140 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: Tony Bennett | Statement: [Teo Macero, collaboratedWith, Tony Bennett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tony Bennett
Context triple: [Teo Macero, collaboratedWith, Tony Bennett]
  • A. Tony Bennett chosen
    Tony Bennett was an American traditional pop and jazz singer renowned for his smooth vocal style and timeless standards like "I Left My Heart in San Francisco."
  • B. Mel Tormé
    Mel Tormé was an American jazz singer, composer, and actor, celebrated for his smooth vocal style and known as "The Velvet Fog."
  • C. Frank Sinatra
    Frank Sinatra was an iconic American singer and actor renowned for his smooth baritone voice, classic pop and jazz recordings, and influential film roles.
  • D. Johnny Hartman
    Johnny Hartman was an American jazz baritone vocalist renowned for his rich, velvety tone and acclaimed collaborations with artists such as John Coltrane.
  • E. Sinatra
    Sinatra is a lightweight Ruby web application framework known for its simple, DSL-based approach to building web services and APIs.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ca5a06481908c7c6b715b9f6713 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a7330c481909e06468be517cf5f completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:51 p.m.