Triple

T19891592
Position Surface form Disambiguated ID Type / Status
Subject Central Province, Zambia E478043 entity
Predicate hasTown P847 FINISHED
Object Serenje NE NERFINISHED

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: Serenje | Statement: [Central Province, Zambia, hasTown, Serenje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serenje
Context triple: [Central Province, Zambia, hasTown, Serenje]
  • A. Serenje chosen
    Serenje is a town in Zambia that serves as an important administrative and transport hub within the country’s Central Province.
  • B. Pomena
    Pomena is a small coastal village and tourist resort on the island of Mljet in southern Croatia, known as a gateway to Mljet National Park.
  • C. Nydri
    Nydri is a popular coastal village and tourist resort on the Greek island of Lefkada, known for its scenic harbor, nearby islets, and vibrant waterfront.
  • D. Sedova
    Sedova is a Russian surname most notably associated with revolutionary figure Natalia Sedova, the second wife of Leon Trotsky.
  • E. Serdinya
    Serdinya is a small commune in the Pyrénées-Orientales department of southern France, situated in the historic region of Conflent in the eastern Pyrenees.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6590ed7988190bc6b610d1f4fa194 completed April 20, 2026, 4:49 p.m.
Created at: April 10, 2026, 1:52 p.m.