Triple

T12491034
Position Surface form Disambiguated ID Type / Status
Subject Carpe Diem E298561 entity
Predicate producer P490 FINISHED
Object ID Cabasa E988134 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: ID Cabasa | Statement: [Carpe Diem, producer, ID Cabasa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ID Cabasa
Context triple: [Carpe Diem, producer, ID Cabasa]
  • A. I.D Cabasa chosen
    I.D Cabasa is a Nigerian record producer and sound engineer best known for shaping the early careers and sounds of several prominent Afrobeats artists.
  • B. Caja
    Caja is the file manager used in the MATE desktop environment, providing users with tools to browse, organize, and manage their files and folders.
  • C. Cabarita
    Cabarita is a riverside suburb in Sydney, New South Wales, known for its waterfront parks and residential areas along the Parramatta River.
  • D. Cabanbanan
    Cabanbanan is a rural barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
  • E. Kabinawa
    Kabinawa is a small settlement located on the atoll of Abemama in the island nation of Kiribati in the central Pacific Ocean.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de3076c81909640c982d520ca6b completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556e9180819084ddb984754b0b54 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 9:56 p.m.