Triple

T9760171
Position Surface form Disambiguated ID Type / Status
Subject k.d. lang E236647 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: [k.d. lang, collaboratedWith, Tony Bennett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tony Bennett
Context triple: [k.d. lang, 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_69ca84d64f6c8190a4ed4e9f5936eda5 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda049995c81908569ec61805642b2 completed April 1, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bce1c5908190a89815fa2b7d90c8 completed April 5, 2026, 1:37 a.m.
Created at: March 30, 2026, 8:25 p.m.