Triple

T14096609
Position Surface form Disambiguated ID Type / Status
Subject Mahra Governorate E339267 entity
Predicate hasBorderTypeWithOman P69016 FINISHED
Object land border 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: land border | Statement: [Mahra Governorate, hasBorderTypeWithOman, land border]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasBorderTypeWithOman
Context triple: [Mahra Governorate, hasBorderTypeWithOman, land border]
  • A. borderTypeWithYemen
    Indicates the type or nature of the border that exists between a given entity and Yemen.
  • B. hadBorderType chosen
    Indicates that a boundary between two entities existed and specifies the nature or classification of that border (e.g., land, maritime, disputed).
  • C. hasBorderFacilityType
    Indicates that a border facility possesses or is classified by a specific type or category of border-related infrastructure or service.
  • D. hasBorderCode
    Indicates that there is an associated code or identifier specifying the type or status of a border between entities.
  • E. hasBorderThrough
    Indicates that a border between two regions or entities passes through or along a specified intermediate area, feature, or object.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5fb926288190a7f0f50d1d585d76 completed April 14, 2026, 3:39 p.m.
PD Predicate disambiguation batch_69de05b2f7e481908a9a7d40153234c0 completed April 14, 2026, 9:15 a.m.
Created at: April 9, 2026, 10:22 p.m.