Triple

T12492725
Position Surface form Disambiguated ID Type / Status
Subject Central Equatoria State E298605 entity
Predicate hasMajorCity P316 FINISHED
Object Terekeka E985838 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: Terekeka | Statement: [Central Equatoria State, hasMajorCity, Terekeka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terekeka
Context triple: [Central Equatoria State, hasMajorCity, Terekeka]
  • A. Terekeka State chosen
    Terekeka State was an administrative region in South Sudan, created from part of Central Equatoria and known for its predominantly rural communities along the White Nile.
  • B. Cherundolo
    Cherundolo is the surname of Steve Cherundolo, a former American soccer player and current coach best known for his long career at Hannover 96 and involvement with the U.S. national team.
  • C. Morrumbene
    Morrumbene is a small town in southern Mozambique known for its rural character within Inhambane Province.
  • D. Karonga
    Karonga is a town in northern Malawi located on the shores of Lake Malawi, known as a regional transport hub and archaeological site.
  • E. Bela-Bela
    Bela-Bela is a South African town in Limpopo Province known for its natural hot mineral springs and tourism-focused resorts.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de3076c81909640c982d520ca6b completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556e9180819084ddb984754b0b54 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 9:56 p.m.