Triple

T3526939
Position Surface form Disambiguated ID Type / Status
Subject Seif Palace E74561 entity
Predicate locatedIn P40 FINISHED
Object Kuwait City E13474 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: Kuwait City | Statement: [Seif Palace, locatedIn, Kuwait City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuwait City
Context triple: [Seif Palace, locatedIn, Kuwait City]
  • A. Kuwait City chosen
    Kuwait City is the capital and largest city of Kuwait, serving as a major political, economic, and cultural center on the Persian Gulf.
  • B. Doha
    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.
  • 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. Kuwait Governorate of Al Asimah
    Kuwait Governorate of Al Asimah is the central administrative region of Kuwait that encompasses the nation’s capital and serves as its political and economic hub.
  • E. Al-Doha
    Al-Doha is a Palestinian town located in the Bethlehem Governorate of the West Bank.
  • 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_69ad85d0c5488190a3d8e02ebd01a1aa completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc6bb0748190bfccfe25d2ab41b7 completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c620ee881908cd766212ee037cb completed March 14, 2026, 8:29 a.m.
Created at: March 8, 2026, 3:19 p.m.