Triple

T10873327
Position Surface form Disambiguated ID Type / Status
Subject Eros Airport E256711 entity
Predicate locatedIn P40 FINISHED
Object Namibia E14828 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: Namibia | Statement: [Eros Airport, locatedIn, Namibia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namibia
Context triple: [Eros Airport, locatedIn, Namibia]
  • A. Namibia chosen
    Namibia is a sparsely populated country in southwestern Africa known for its dramatic desert landscapes, diverse wildlife, and a legal system influenced by Roman-Dutch law.
  • B. Botswana
    Botswana is a landlocked country in Southern Africa known for its stable democracy, significant diamond resources, and vast wildlife-rich landscapes including the Okavango Delta.
  • C. Namibia and Botswana
    Namibia and Botswana are neighboring countries in Southern Africa known for their vast deserts, rich wildlife, and major river systems that shape their shared ecosystems and borders.
  • D. Eswatini
    Eswatini is a small landlocked monarchy in Southern Africa known for its blend of traditional Swazi culture and modern institutions.
  • E. Zimbabwe
    Zimbabwe is a landlocked country in southern Africa known for its dramatic landscapes, diverse wildlife, and historical sites such as Victoria Falls and the Great Zimbabwe ruins.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751891b508190959784f212e06acb completed April 9, 2026, 7:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69e154d8f9b881908025acc6ff1beb9f completed April 16, 2026, 9:30 p.m.
Created at: April 8, 2026, 9:21 p.m.