Triple

T14512323
Position Surface form Disambiguated ID Type / Status
Subject African Union Mission in Somalia (AMISOM) forces E340427 entity
Predicate contributingCountry P835 FINISHED
Object Kenya E11292 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: Kenya | Statement: [African Union Mission in Somalia (AMISOM) forces, contributingCountry, Kenya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenya
Context triple: [African Union Mission in Somalia (AMISOM) forces, contributingCountry, Kenya]
  • A. Kenya chosen
    Kenya is an East African country known for its diverse wildlife, scenic landscapes from savannas to highlands, and a coastline along the Indian Ocean.
  • B. Nyeri, Kenya
    Nyeri, Kenya is a town in central Kenya near the Aberdare Range, known for its colonial-era history, agricultural economy, and as the final resting place of Scouting founder Robert Baden-Powell.
  • C. Kamba (Kenya)
    Kamba (Kenya) is a Bantu language spoken primarily by the Kamba people in eastern Kenya.
  • D. Uganda
    Uganda is a landlocked country in East Africa known for its diverse landscapes, abundant wildlife, and location along the equator.
  • E. Tanzania
    Tanzania is an East African nation known for its vast wilderness areas, including the Serengeti National Park and Mount Kilimanjaro, as well as its rich cultural diversity.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a6c6054819086b4c0ce1d83fdc5 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6da48b2c8190a906965a7ebcb607 completed May 8, 2026, 4:59 a.m.
Created at: April 10, 2026, 1:21 a.m.