Triple

T4598739
Position Surface form Disambiguated ID Type / Status
Subject Architecture-Studio E100268 entity
Predicate hasOfficeIn P1268 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: [Architecture-Studio, hasOfficeIn, Doha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doha
Context triple: [Architecture-Studio, hasOfficeIn, 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_69bd43cbc014819098b45f435908f88a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd59707f8c8190b8368f1de887ff2a completed March 20, 2026, 2:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa4f26d08190b9978c579623adcb completed March 21, 2026, 1:54 a.m.
Created at: March 20, 2026, 1:11 p.m.