Triple

T763075
Position Surface form Disambiguated ID Type / Status
Subject Eritrea E16113 entity
Predicate largestCity P235 FINISHED
Object Asmara E92266 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: Asmara | Statement: [Eritrea, largestCity, Asmara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asmara
Context triple: [Eritrea, largestCity, Asmara]
  • A. Asmara chosen
    Asmara is the largest city of Eritrea, known for its well-preserved Italian colonial modernist architecture and status as a UNESCO World Heritage Site.
  • B. Djibouti City
    Djibouti City is the largest urban center and main economic, political, and cultural hub of the Republic of Djibouti, located on the Gulf of Tadjoura in the Horn of Africa.
  • C. Addis Ababa
    Addis Ababa is the capital and largest city of Ethiopia, serving as a major political and diplomatic hub in Africa that hosts numerous international organizations and institutions.
  • D. Tripoli
    Tripoli is a historic Mediterranean port city that serves as the capital and largest urban center of Libya.
  • E. Tripoli
    Tripoli is Lebanon’s second-largest city, a historic Mediterranean port known for its medieval Mamluk architecture and vibrant commercial life.
  • 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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a6841f388190a6d08c3bf5c17fe4 completed March 1, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6733773588190885d03d714e21b37 completed March 3, 2026, 5:35 a.m.
Created at: March 1, 2026, 7:37 p.m.