Triple

T23150831
Position Surface form Disambiguated ID Type / Status
Subject Black Desert E578317 entity
Predicate near P350 FINISHED
Object White Desert NE NERFINISHED

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: White Desert | Statement: [Black Desert, near, White Desert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: White Desert
Context triple: [Black Desert, near, White Desert]
  • A. White Desert chosen
    White Desert is a striking desert region in Egypt famed for its surreal white chalk rock formations and otherworldly landscapes.
  • B. The White Desert
    The White Desert is a novel by British author Noel Barber, known for its blend of historical detail and romantic adventure set against an exotic backdrop.
  • C. The Desert
    "The Desert" is a luminous 19th-century landscape painting by American artist Sanford Robinson Gifford, exemplifying the Hudson River School’s atmospheric treatment of light and expansive natural vistas.
  • D. Deadly Desert
    The Deadly Desert is a vast, impassable wasteland of lethal sands that isolates the magical Land of Oz from the surrounding world in L. Frank Baum’s Oz series.
  • E. Sea of Sand
    The Sea of Sand is a vast, otherworldly volcanic sand plain surrounding Mount Bromo in East Java, Indonesia, renowned for its stark, lunar-like landscape.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245fb8de081908f0eba7b5fd75bc4 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18ed1a258819091ce86dbd1c51e46 completed April 29, 2026, 4:53 a.m.
Created at: April 17, 2026, 4:01 p.m.