Triple

T12715167
Position Surface form Disambiguated ID Type / Status
Subject Owerri West E303817 entity
Predicate sharesBorderWith P224 FINISHED
Object Aboh Mbaise E295904 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: Aboh Mbaise | Statement: [Owerri West, sharesBorderWith, Aboh Mbaise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aboh Mbaise
Context triple: [Owerri West, sharesBorderWith, Aboh Mbaise]
  • A. Aboh Mbaise chosen
    Aboh Mbaise is a local government area in southeastern Nigeria known for its predominantly Igbo population and rich cultural traditions.
  • B. Ahiazu Mbaise
    Ahiazu Mbaise is a local government area in southeastern Nigeria known for its predominantly Igbo population and rich cultural traditions.
  • C. Ezinihitte Mbaise
    Ezinihitte Mbaise is a local government area in southeastern Nigeria known for its predominantly Igbo population and rich cultural traditions within Imo State.
  • D. Arinze
    Arinze is a Nigerian surname most notably borne by Cardinal Francis Arinze, a prominent figure in the Roman Catholic Church.
  • E. Igbesa
    Igbesa is a prominent town in Ogun State, Nigeria, known for its growing industrial presence and educational institutions.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9620a7554819083784897ff690652 completed April 10, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fef8d94081908ea5ac426e22ef87 completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 5:23 p.m.