Triple

T3990251
Position Surface form Disambiguated ID Type / Status
Subject Skeleton Coast E86971 entity
Predicate partOf P40 FINISHED
Object Namib Desert E14396 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: Namib Desert | Statement: [Skeleton Coast, partOf, Namib Desert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Namib Desert
Context triple: [Skeleton Coast, partOf, Namib Desert]
  • A. Namib Desert chosen
    The Namib Desert is a vast, ancient coastal desert in southwestern Africa, renowned for its towering red sand dunes and extreme arid conditions along the Atlantic coast.
  • B. Kalahari Desert
    The Kalahari Desert is a vast semi-arid sandy savanna in southern Africa known for its red dunes, sparse vegetation, and unique wildlife adapted to its dry conditions.
  • C. Kalimari Desert
    Kalimari Desert is a Wild West–themed racetrack in the Mario Kart series, characterized by its sandy terrain and a central railroad crossing with an active train obstacle.
  • D. Błędów Desert
    Błędów Desert is a rare inland sand desert in southern Poland, known for its extensive dunes and unique, almost desert-like landscape.
  • E. Sahara Desert
    The Sahara Desert is the world’s largest hot desert, spanning much of North Africa with vast sand seas, rocky plateaus, and extreme arid conditions.
  • 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa01bf3c8190a6fb3bba65186ae6 completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c50f348819090ebfd8b5192c819 completed March 14, 2026, 11:53 a.m.
Created at: March 9, 2026, 3:33 p.m.