Triple

T7261408
Position Surface form Disambiguated ID Type / Status
Subject Pêro da Covilhã E159660 entity
Predicate visited P2694 FINISHED
Object Aden E22158 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: Aden | Statement: [Pêro da Covilhã, visited, Aden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aden
Context triple: [Pêro da Covilhã, visited, Aden]
  • A. Aden chosen
    Aden is a strategic port city in Yemen located on the Gulf of Aden, historically significant as a major maritime hub and former British colonial stronghold.
  • B. Salalah
    Salalah is a coastal city in southern Oman known for its monsoon-cooled climate, lush green landscapes, and role as a regional tourism and commercial hub.
  • C. Al Hudaydah
    Al Hudaydah is a key Red Sea port city in western Yemen that serves as one of the country’s main commercial and strategic hubs.
  • D. Sanaʽa
    Sanaʽa is the historic capital and one of the largest cities of Yemen, renowned for its ancient architecture and cultural significance in the Arabian Peninsula.
  • E. Arafo
    Arafo is a small municipality on the island of Tenerife in Spain’s Canary Islands, known for its rural landscapes and traditional Canarian character.
  • 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_69c68838f9948190875fd60b2351230c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eac79fd081909274aa10ffb192aa completed March 27, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d3bda4808190810f2d170cb693b9 completed March 28, 2026, 1:12 p.m.
Created at: March 27, 2026, 2:57 p.m.