Triple

T20128355
Position Surface form Disambiguated ID Type / Status
Subject Lorenzo Daza E490817 entity
Predicate familyName P18 FINISHED
Object Daza 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: Daza | Statement: [Lorenzo Daza, familyName, Daza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daza
Context triple: [Lorenzo Daza, familyName, Daza]
  • A. Daza chosen
    The Daza are an ethnic group of the central Sahara, primarily in Chad, known for their nomadic pastoralist lifestyle and close cultural and linguistic ties to the Toubou (Tebu) peoples.
  • B. Zazai
    Zazai is a Pashtun tribe associated with the Karlani tribal confederation, primarily found in eastern Afghanistan and parts of Pakistan.
  • C. Chakiwara
    Chakiwara is a residential neighborhood located within Lyari Town in Karachi, Pakistan, known for its dense urban character and vibrant local culture.
  • D. Sawa
    Sawa is a Japanese surname most prominently associated with Homare Sawa, a legendary Japanese women’s footballer and World Cup winner.
  • E. Adenzai
    Adenzai is a town and administrative settlement located in the Lower Dir District of Khyber Pakhtunkhwa province in Pakistan.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6675fe3d48190b0c20b483a951e68 completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:31 p.m.