Triple

T13077934
Position Surface form Disambiguated ID Type / Status
Subject Mountains of the Moon E329626 entity
Predicate contains P35 FINISHED
Object Mount Gessi E359640 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: Mount Gessi | Statement: [Mountains of the Moon, contains, Mount Gessi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Gessi
Context triple: [Mountains of the Moon, contains, Mount Gessi]
  • A. Mount Gessi chosen
    Mount Gessi is one of the prominent high peaks in the Rwenzori Mountains range of East Africa, known for its rugged alpine terrain and glaciated landscape.
  • B. Mount Egon
    Mount Egon is an active stratovolcano located on the island of Flores in Indonesia, known for its periodic eruptions and geothermal activity.
  • C. Mount Gazanasar
    Mount Gazanasar is a notable summit within the Zangezur mountain range in the South Caucasus region.
  • D. Mount Giona
    Mount Giona is a prominent mountain massif in central Greece known for its rugged terrain and significant elevation among the country’s highest peaks.
  • E. Mount Wilis
    Mount Wilis is a solitary, inactive stratovolcano in East Java, Indonesia, known for its forested slopes and surrounding rural highland communities.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d9811828448190ac6ddd3e9c221251 completed April 10, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a227d2c81908da0089d0e0387c6 completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:01 p.m.