Triple

T5607667
Position Surface form Disambiguated ID Type / Status
Subject Milo E147271 entity
Predicate popularInCountry P2352 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: [Milo, popularInCountry, Kenya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenya
Context triple: [Milo, popularInCountry, 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. Uganda
    Uganda is a landlocked country in East Africa known for its diverse landscapes, abundant wildlife, and location along the equator.
  • C. 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.
  • D. Rwanda
    Rwanda is a landlocked East African nation known for its dramatic recovery from the 1994 genocide, rapid economic growth, and strong conservation efforts, particularly for mountain gorillas.
  • E. Central Province, Kenya
    Central Province, Kenya was a former administrative region in central Kenya known for its fertile highlands, tea and coffee production, and predominantly Kikuyu population.
  • 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_69c0090500f881908374285baf0ac46f completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020fd1b2c81908da154f7e11b90d8 completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c02873b1dc8190b11a6c069f3e4f7e completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:39 p.m.