Triple

T14348453
Position Surface form Disambiguated ID Type / Status
Subject Katara Mosque E355789 entity
Predicate locatedIn P40 FINISHED
Object Doha, Qatar 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, Qatar | Statement: [Katara Mosque, locatedIn, Doha, Qatar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doha, Qatar
Context triple: [Katara Mosque, locatedIn, Doha, Qatar]
  • 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. Doha district
    Doha district is an urban administrative area within Kuwait’s capital region, forming part of the metropolitan core of Kuwait City.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e8d081c8190ac805726a3e98f4c completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd550aef908190a7ec49e409f92dc7 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:14 a.m.