Triple

T2484514
Position Surface form Disambiguated ID Type / Status
Subject Chichewa E55892 entity
Predicate closelyRelatedTo P37 FINISHED
Object Sena E79208 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: Sena | Statement: [Chichewa, closelyRelatedTo, Sena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sena
Context triple: [Chichewa, closelyRelatedTo, Sena]
  • A. Sena chosen
    Sena is a Bantu language spoken primarily along the Zambezi River region of central Mozambique and parts of neighboring countries.
  • B. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • C. Beni
    Beni is a city in the eastern Democratic Republic of the Congo that became internationally known as a major hotspot of conflict and public health crises, including serving as the epicenter of the 2018–2020 Kivu Ebola epidemic.
  • D. Beni
    Beni is a town in western Nepal that serves as a gateway to the Dhaulagiri and Annapurna mountain regions.
  • E. Senaki
    Senaki is a town in western Georgia that serves as an important local administrative and transportation center in the Samegrelo region.
  • 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd175f5ac8190870db9c6cb8e45bd completed March 7, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17b7b4f08190b23af81c696bba4e completed March 9, 2026, 6:55 p.m.
Created at: March 6, 2026, 9:45 p.m.