Triple

T12138136
Position Surface form Disambiguated ID Type / Status
Subject Mount Tambuyukon E289113 entity
Predicate rankingByElevationInMalaysia P87950 FINISHED
Object third-highest mountain in Malaysia LITERAL 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: third-highest mountain in Malaysia | Statement: [Mount Tambuyukon, rankingByElevationInMalaysia, third-highest mountain in Malaysia]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rankingByElevationInMalaysia
Context triple: [Mount Tambuyukon, rankingByElevationInMalaysia, third-highest mountain in Malaysia]
  • A. regionRankByHeight chosen
    Indicates the relative ordering of regions based on their height or elevation.
  • B. countryRankByHeight
    Indicates the relative position of a country when countries are ordered by the height of something (e.g., average elevation, tallest point, or average citizen height).
  • C. countryAltitudeCharacteristic
    Indicates a characteristic relationship specifying the typical or notable altitude or elevation associated with a country.
  • D. peakElevationMetres
    Indicates the maximum height of an entity above sea level, measured in metres.
  • E. countryHighestPointAccess
    Indicates that an entity has access to, or the ability to reach or utilize, the highest geographical point within a specified country.
  • F. None of above.

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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d91841615c819097f20a7447a1b8f4 completed April 10, 2026, 3:33 p.m.
PD Predicate disambiguation batch_69d91508f8008190b3a90ec0bf0953ca completed April 10, 2026, 3:19 p.m.
Created at: April 8, 2026, 9:49 p.m.