Triple

T19075247
Position Surface form Disambiguated ID Type / Status
Subject UCCI E466885 entity
Predicate hasMember P10 FINISHED
Object Bissau 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: Bissau | Statement: [UCCI, hasMember, Bissau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bissau
Context triple: [UCCI, hasMember, Bissau]
  • A. Bissau chosen
    Bissau is the largest city and principal port of Guinea-Bissau, serving as its political, economic, and cultural center.
  • B. Bissau
    Bissau is a town in the Jhunjhunu district of Rajasthan, India, known for its historic havelis and traditional Rajasthani culture.
  • C. Conakry
    Conakry is the capital and largest city of Guinea, serving as its main economic, cultural, and administrative center on the Atlantic coast of West Africa.
  • D. Navrongo
    Navrongo is a town in northern Ghana known as a key administrative and commercial center near the border with Burkina Faso.
  • E. Korhogo
    Korhogo is a major city in northern Côte d'Ivoire that serves as an important cultural and economic center for the Senufo people.
  • 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_69d8dd04f4488190b1121cc53ef2bfd6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e2e3c7b08190bf6448ead11ba916 completed April 20, 2026, 8:25 a.m.
Created at: April 10, 2026, 12:04 p.m.