Triple

T9213625
Position Surface form Disambiguated ID Type / Status
Subject Jose E221185 entity
Predicate includesSingle P11236 FINISHED
Object Tu Veneno E785488 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: Tu Veneno | Statement: [Jose, includesSingle, Tu Veneno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tu Veneno
Context triple: [Jose, includesSingle, Tu Veneno]
  • A. Tu Veneno chosen
    "Tu Veneno" is a popular Latin pop song best known as a hit single by Argentine singer Natalia Oreiro.
  • B. Le Poison
    Le Poison is a poem by Charles Baudelaire, featured in his collection "Les Fleurs du mal," that explores themes of intoxication, desire, and destructive passion.
  • C. Pretty Poison
    Pretty Poison is a 1968 darkly comic psychological thriller film best known for its unsettling blend of romance and violence and for featuring Anthony Perkins in a memorable post-Psycho role.
  • D. A Vow to Kill
    A Vow to Kill is a 1995 made-for-television thriller film starring Julianne Phillips as a woman whose seemingly perfect marriage turns dangerously deadly.
  • E. Big Poison
    Big Poison was the nickname of Paul Waner, a Hall of Fame Major League Baseball outfielder renowned for his exceptional hitting with the Pittsburgh Pirates in the 1920s and 1930s.
  • 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_69ca83eae42c8190a0ea9e040710a277 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda06bf80819094c6e74b4b6a31e4 completed April 1, 2026, 8:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0778e8dc48190bbae39137df966e3 completed April 4, 2026, 2:29 a.m.
Created at: March 30, 2026, 7:27 p.m.