Triple

T10295236
Position Surface form Disambiguated ID Type / Status
Subject Devil’s Pool E241467 entity
Predicate languageLocal P18209 FINISHED
Object Nyanja E136466 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: Nyanja | Statement: [Devil’s Pool, languageLocal, Nyanja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nyanja
Context triple: [Devil’s Pool, languageLocal, Nyanja]
  • A. Nyanja chosen
    Nyanja is a major Bantu language spoken primarily in Malawi, Zambia, Mozambique, and Zimbabwe, known for serving as a lingua franca in parts of southern Africa.
  • B. Kasindi
    Kasindi is a border town in eastern Democratic Republic of the Congo, located near Uganda and serving as an important regional trade and transport hub.
  • C. Kigoma
    Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
  • D. Wazaramo
    Wazaramo are a Bantu-speaking ethnic group native to the coastal and near-coastal regions around Dar es Salaam in eastern Tanzania.
  • E. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2d5e0f88190be3e23ba2511a1e9 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d23f49081909aea149c6b219354 completed April 9, 2026, 3:29 a.m.
Created at: April 6, 2026, 11:43 a.m.