Triple

T5515411
Position Surface form Disambiguated ID Type / Status
Subject Amanat Al Asimah Governorate E144670 entity
Predicate contains P35 FINISHED
Object Sanaʽa E15731 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: Sanaʽa | Statement: [Amanat Al Asimah Governorate, contains, Sanaʽa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sanaʽa
Context triple: [Amanat Al Asimah Governorate, contains, Sanaʽa]
  • A. Sanaʽa chosen
    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.
  • B. Sanaa
    Sanaa is a table-service restaurant at Disney’s Animal Kingdom Lodge known for its African-inspired cuisine with Indian flavors and savanna views of roaming wildlife.
  • C. 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.
  • D. Taiz
    Taiz is one of Yemen’s largest and historically most important cities, known as a cultural and intellectual center in the country.
  • E. SANAA
    SANAA is a renowned Japanese architectural firm, led by Kazuyo Sejima and Ryue Nishizawa, celebrated for its minimalist, light-filled designs and influential contemporary projects worldwide.
  • 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_69c008f77ff88190b0cd50ca207295d1 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f5d1d188190b3a222a9ecf2a0e6 completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04cc5f37881909f9aa8090f6c9685 completed March 22, 2026, 8:10 p.m.
Created at: March 22, 2026, 3:33 p.m.