Triple

T12823179
Position Surface form Disambiguated ID Type / Status
Subject Doha Bay E306582 entity
Predicate hasShoreOn P26435 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: [Doha Bay, hasShoreOn, Doha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doha
Context triple: [Doha Bay, hasShoreOn, 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-Doha
    Al-Doha is a Palestinian town located in the Bethlehem Governorate of the West Bank.
  • C. Al Rayyan
    Al Rayyan is a major Qatari city known for its rapid urban development, sports facilities, and proximity to the capital, Doha.
  • D. 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.
  • E. 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.
  • 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e9fcc8c8190a926ab0481d28f14 completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b99d9bc8190b67f73985c8f6768 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:32 p.m.