Triple

T21935343
Position Surface form Disambiguated ID Type / Status
Subject Real Hasta la Muerte E541671 entity
Predicate hasProducer P30366 FINISHED
Object Foreign Teck NE NERFINISHED

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: Foreign Teck | Statement: [Real Hasta la Muerte, hasProducer, Foreign Teck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Foreign Teck
Context triple: [Real Hasta la Muerte, hasProducer, Foreign Teck]
  • A. Foreign Teck chosen
    Foreign Teck is a hip-hop record producer known for crafting hard-hitting, melodic beats for prominent rap artists.
  • B. Tehkal
    Tehkal is a neighborhood and administrative area within the city of Peshawar in Pakistan’s Khyber Pakhtunkhwa province.
  • C. Soon-Tek
    Soon-Tek is the given name of Soon-Tek Oh, a Korean-American actor known for his roles in film, television, and voice acting.
  • D. TEC
    TEC is a public transport company in Belgium that operates regional bus and other transit services, primarily in the Walloon region.
  • E. TEC
    TEC is the abbreviation for the Transatlantic Economic Council, a high-level forum for coordinating economic policy and regulatory cooperation between the United States and the European Union.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47e2e5c81909a7f74ce3de50911 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f124048fe48190987340d5a6945176 completed April 28, 2026, 9:17 p.m.
Created at: April 16, 2026, 7:52 p.m.