Triple

T10777192
Position Surface form Disambiguated ID Type / Status
Subject Aniocha South E254228 entity
Predicate hasSettlement P1068 FINISHED
Object Nsukwa E884087 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: Nsukwa | Statement: [Aniocha South, hasSettlement, Nsukwa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nsukwa
Context triple: [Aniocha South, hasSettlement, Nsukwa]
  • A. Nsukwa chosen
    Nsukwa is a town in Aniocha South Local Government Area of Delta State, Nigeria, known as one of the traditional Igbo communities in the region.
  • B. Kolwezi
    Kolwezi is a mining city in the southern Democratic Republic of the Congo, known for its rich copper and cobalt deposits and its role as a major industrial and economic center in the Lualaba province.
  • C. Soroti
    Soroti is a town in eastern Uganda that serves as a regional commercial and administrative center.
  • D. Butembo
    Butembo is a major commercial city in eastern Democratic Republic of the Congo, known as a trading hub and economic center in North Kivu.
  • E. Kasese
    Kasese is a town in western Uganda that serves as a key gateway to Queen Elizabeth National Park and the Rwenzori Mountains.
  • 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_69de55daf52c8190aee3bca39cdc5d55 completed April 14, 2026, 2:57 p.m.
Created at: April 8, 2026, 9:16 p.m.