Triple

T4226586
Position Surface form Disambiguated ID Type / Status
Subject Móstoles E94472 entity
Predicate hasTwinTown P919 FINISHED
Object Lusaka E31817 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: Lusaka | Statement: [Móstoles, hasTwinTown, Lusaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lusaka
Context triple: [Móstoles, hasTwinTown, Lusaka]
  • A. Lusaka, Zambia chosen
    Lusaka, Zambia is the capital and largest city of Zambia, serving as the country’s political, economic, and cultural center.
  • B. Lilongwe
    Lilongwe is the largest city and administrative and political center of Malawi, located in the country’s central region.
  • C. Matadi
    Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
  • D. Kasane
    Kasane is a small town in northern Botswana that serves as a key gateway and service hub for visitors to Chobe National Park and the surrounding wildlife areas.
  • E. Kabwe, Zambia
    Kabwe, Zambia is a central Zambian town historically known as a major mining and railway hub and as the birthplace of novelist Wilbur Smith.
  • 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_69b3453700a08190ae88792e3dc63207 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e4ed34c819081d1479ce87cd78c completed March 12, 2026, 11:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5964a388881908038e5a612424b9b completed March 14, 2026, 5:09 p.m.
Created at: March 12, 2026, 11:04 p.m.