Triple

T2677324
Position Surface form Disambiguated ID Type / Status
Subject President of the Senate of Nigeria E56490 entity
Predicate residence P75 FINISHED
Object Abuja E9148 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: Abuja | Statement: [President of the Senate of Nigeria, residence, Abuja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abuja
Context triple: [President of the Senate of Nigeria, residence, Abuja]
  • A. Abuja chosen
    Abuja is a planned city in central Nigeria that serves as the country’s political and administrative center.
  • B. Lagos
    Lagos is a major coastal megacity in southwestern Nigeria, known as the country’s economic hub and one of Africa’s most populous and vibrant urban centers.
  • C. Lagos
    Lagos is a historic coastal city in Portugal’s Algarve region, known for its scenic beaches, dramatic cliffs, and well-preserved old town.
  • D. Ibadan
    Ibadan is one of the largest and most populous cities in southwestern Nigeria, historically significant as a major Yoruba cultural and economic center.
  • E. Makurdi
    Makurdi is the capital city of Benue State in central Nigeria, serving as an important administrative and commercial hub in the region.
  • 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_69ab4a4b13fc81909dfdb3f23da46832 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9b697fc8190a5ec8b75ee2ad238 completed March 7, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc02d8730819093a576d3751432de completed March 10, 2026, 6:54 a.m.
Created at: March 6, 2026, 9:54 p.m.