Triple

T25699526
Position Surface form Disambiguated ID Type / Status
Subject Nairobi–Dar es Salaam E644417 entity
Predicate crossesInternationalBorderBetween P124722 FINISHED
Object Kenya and Tanzania LITERAL 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 and Tanzania | Statement: [Nairobi–Dar es Salaam, crossesInternationalBorderBetween, Kenya and Tanzania]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: crossesInternationalBorderBetween
Context triple: [Nairobi–Dar es Salaam, crossesInternationalBorderBetween, Kenya and Tanzania]
  • A. crossesInternationalBoundaryAt chosen
    Indicates that one entity passes from one country’s territory into another at a specific boundary location.
  • B. crossesBorderOf
    Indicates that one entity passes from one side of the boundary of another entity (typically a region or area) to the other side, traversing its border.
  • C. hasBorderCrossing
    Indicates that there exists a point or facility where movement or transit is possible between the boundaries of two adjacent regions or jurisdictions.
  • D. borderStateAcrossInternationalBorder
    Indicates that one state shares a boundary with another state across an international border.
  • E. borderTownAcrossBorder
    Indicates that a town lies on one side of a border directly opposite or adjacent to a town on the other side of that border.
  • F. None of above.

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_69e77e82c9bc8190893090b2f6c64f1d completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fbc7c004819088a2450a4749c5e0 completed May 2, 2026, 1:27 p.m.
PD Predicate disambiguation batch_69f4938262ac8190b41f922d0407d272 completed May 1, 2026, 11:50 a.m.
Created at: April 21, 2026, 8:42 p.m.