Triple

T1477088
Position Surface form Disambiguated ID Type / Status
Subject Persian Gulf states E30864 entity
Predicate hasKeyPortCity P2745 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: [Persian Gulf states, hasKeyPortCity, Doha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doha
Context triple: [Persian Gulf states, hasKeyPortCity, 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. Al Rayyan
    Al Rayyan is a major Qatari city known for its rapid urban development, sports facilities, and proximity to the capital, Doha.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c9e02c188190b87c0aac939eafdd completed March 1, 2026, 11:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad15add78c8190843efd75bbe8423f completed March 8, 2026, 6:22 a.m.
Created at: March 1, 2026, 8:11 p.m.