Triple

T3248201
Position Surface form Disambiguated ID Type / Status
Subject National Museum of Qatar E68113 entity
Predicate owner P347 FINISHED
Object State of Qatar E13453 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: State of Qatar | Statement: [National Museum of Qatar, owner, State of Qatar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: State of Qatar
Context triple: [National Museum of Qatar, owner, State of Qatar]
  • A. Qatar chosen
    Qatar is a wealthy Gulf nation on the Arabian Peninsula known for its vast natural gas reserves, rapid modernization, and large expatriate workforce.
  • B. Kuwait
    Kuwait is a small, oil-rich Gulf nation on the Arabian Peninsula known for its modern capital Kuwait City, significant expatriate workforce, and strategic geopolitical importance.
  • C. Bahrain
    Bahrain is a small island nation in the Persian Gulf known for its rich history, oil wealth, and status as a regional financial and cultural hub.
  • D. Bahrain
    Bahrain is a popular riverside town and tourist destination in Pakistan’s Swat Valley, known for its scenic beauty and as a base for exploring nearby mountain areas.
  • E. United Arab Emirates
    The United Arab Emirates is a wealthy Gulf nation on the Arabian Peninsula known for its rapid modernization, iconic cities like Dubai and Abu Dhabi, and its large expatriate workforce.
  • 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_69ad858e4c708190aa31d486cfee8a6a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf3e9ed0819096ac238098ac403c completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4dae9a0cc8190acc56eaa4f2479ef completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:09 p.m.