Triple

T10777198
Position Surface form Disambiguated ID Type / Status
Subject Aniocha South E254228 entity
Predicate hasSettlement P1068 FINISHED
Object Ewulu E886213 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: Ewulu | Statement: [Aniocha South, hasSettlement, Ewulu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ewulu
Context triple: [Aniocha South, hasSettlement, Ewulu]
  • A. Ewulu chosen
    Ewulu is a town in Aniocha South Local Government Area of Delta State, Nigeria, known as one of the Igbo communities in the region.
  • B. Wele-Nzas
    Wele-Nzas is a province in mainland Equatorial Guinea known for its forests, border location near Gabon and Cameroon, and the city of Mongomo.
  • C. Ikwerre
    Ikwerre is a Niger-Congo language spoken primarily by the Ikwerre people in Rivers State, Nigeria, particularly in and around Port Harcourt.
  • D. Ewondo
    Ewondo is a Bantu language spoken primarily by the Ewondo people in central Cameroon, including in and around the capital city, Yaoundé.
  • E. Weija
    Weija is a suburban community in the Greater Accra Region of Ghana, known for the Weija Dam and its role in supplying water to Accra and surrounding areas.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7329d8c908190bddad40685133ea1 completed April 9, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb0b5c9d8819088edb21a35d8b0dc completed April 14, 2026, 9:25 p.m.
Created at: April 8, 2026, 9:16 p.m.