Triple

T552849
Position Surface form Disambiguated ID Type / Status
Subject Qatar Airways E11877 entity
Predicate cityServed P82 FINISHED
Object Doha E12693 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: Doha | Statement: [Qatar Airways, cityServed, Doha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doha
Context triple: [Qatar Airways, cityServed, Doha]
  • A. Doha chosen
    Doha is the rapidly developing capital and largest city of Qatar, known for its modern skyline, cultural institutions, and role as a major political and economic center in the Arab world.
  • B. Abu Dhabi
    Abu Dhabi is the capital and second-most populous city of the United Arab Emirates, known for its vast oil wealth, modern skyline, and role as a major political and economic center in the Arab world.
  • C. Kuwait City
    Kuwait City is the capital and largest city of Kuwait, serving as a major political, economic, and cultural center on the Persian Gulf.
  • D. Dubai
    Dubai is a major global city in the United Arab Emirates known for its rapid development, luxury tourism, and status as a regional business and financial hub.
  • E. Sharjah
    Sharjah is a major cultural and economic center in the United Arab Emirates, known for its rich heritage, museums, and role as a hub of Islamic arts and education.
  • 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_69a4932941d08190815efd422f0b4ca7 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4991b296481908cf27e1d1ec67052 completed March 1, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69a57b51a58481909d8e602b3fe3c68c completed March 2, 2026, 11:58 a.m.
Created at: March 1, 2026, 7:32 p.m.