Triple

T16446715
Position Surface form Disambiguated ID Type / Status
Subject Mwadi Mabika E399448 entity
Predicate givenName P17 FINISHED
Object Mwadi E399448 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: Mwadi | Statement: [Mwadi Mabika, givenName, Mwadi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mwadi
Context triple: [Mwadi Mabika, givenName, Mwadi]
  • A. Mwadi Mabika chosen
    Mwadi Mabika is a former Congolese professional basketball player best known as a standout guard for the Los Angeles Sparks in the WNBA.
  • B. Gilgil River
    Gilgil River is a freshwater river in Kenya’s Rift Valley that feeds into Lake Naivasha and supports surrounding agricultural and wildlife ecosystems.
  • C. Moawhango River
    The Moawhango River is a river in New Zealand’s central North Island that flows through rugged hill country and feeds into the larger Rangitīkei River system.
  • D. Ruza River
    The Ruza River is a waterway in western Russia that serves as one of the tributaries feeding into the Moskva River.
  • E. Mangamma
    Mangamma is an Indian surname commonly associated with South Indian families and traditional given names.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32cdcedf8819080aa82a8712c0b42 completed April 18, 2026, 7:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ecfd99c8190a4375a0f62aa50d1 completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:10 a.m.