Triple

T7209918
Position Surface form Disambiguated ID Type / Status
Subject Charmbracelet E148774 entity
Predicate producer P490 FINISHED
Object Damizza E536173 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: Damizza | Statement: [Charmbracelet, producer, Damizza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Damizza
Context triple: [Charmbracelet, producer, Damizza]
  • A. Damizza chosen
    Damizza is an American hip hop and R&B record producer and radio executive known for his work with major artists in the late 1990s and early 2000s.
  • B. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • C. Temara
    Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
  • D. Dorla
    Dorla are an indigenous Adivasi community of the Bastar region in central India, known for their distinct cultural traditions, language, and close relationship with forest-based livelihoods.
  • E. Boghni
    Boghni is a town and commune in northern Algeria’s Kabylie region, known for its Berber (Amazigh) cultural heritage and mountainous surroundings.
  • 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_69c687e8cf188190b5f3ecffd681f04e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e96c46dc819080a6b40456d7b068 completed March 27, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bfc4e6688190ad9e0d31505e65af completed March 28, 2026, 11:47 a.m.
Created at: March 27, 2026, 2:53 p.m.