Triple

T2885583
Position Surface form Disambiguated ID Type / Status
Subject Bukhara E59496 entity
Predicate historicalRegion P915 FINISHED
Object Mawarannahr E67423 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: Mawarannahr | Statement: [Bukhara, historicalRegion, Mawarannahr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mawarannahr
Context triple: [Bukhara, historicalRegion, Mawarannahr]
  • A. Azania
    Azania is a name used by some African liberation movements and activists to refer to a decolonized, non-apartheid South Africa.
  • B. Khorasan chosen
    Khorasan is a historical region in northeastern Iran and surrounding areas that served as a major cultural and political center in various Persian and Islamic empires.
  • C. Negaraku
    Negaraku is the national anthem of Malaysia, symbolizing the country's sovereignty and unity.
  • D. Karas Region
    Karas Region is the southernmost administrative region of Namibia, known for its arid landscapes, desert scenery, and coastal towns along the Atlantic Ocean.
  • E. Ngchesar State
    Ngchesar State is one of the states of Palau, located on the island of Babeldaob and known for its traditional villages and coastal mangrove forests.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe04476588190b0db0880e14c79b5 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b031713e14819098db4cfaaea74f73 completed March 10, 2026, 2:57 p.m.
Created at: March 6, 2026, 10:03 p.m.