Triple

T1873608
Position Surface form Disambiguated ID Type / Status
Subject Malay Peninsula E39088 entity
Predicate highestPoint P210 FINISHED
Object Mount Tahan E210532 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 Tahan | Statement: [Malay Peninsula, highestPoint, Mount Tahan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Tahan
Context triple: [Malay Peninsula, highestPoint, Mount Tahan]
  • A. Mount Tahan chosen
    Mount Tahan is the highest peak on the Malay Peninsula, located within Malaysia’s Taman Negara National Park and renowned for its challenging jungle treks.
  • B. Mount Welirang
    Mount Welirang is an active stratovolcano in East Java, Indonesia, known for its sulfur mining and frequent fumarolic activity.
  • C. Mount Papandayan
    Mount Papandayan is an active stratovolcano in West Java, Indonesia, known for its steaming fumaroles, sulfur craters, and popular hiking trails.
  • D. Mount Heha
    Mount Heha is the tallest mountain in Burundi, located in the Burundi Highlands near the city of Bujumbura.
  • E. Mount Vitsi
    Mount Vitsi is a mountain in northern Greece near the border with Albania, known for its strategic role in the Greek Civil War and its forested slopes that now attract hikers and nature enthusiasts.
  • 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_69a8862f7074819096afe7fe65e179e9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0d648ec8190a21445ddca6f9aa6 completed March 7, 2026, 5 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeae228008190a0d427c74fd37511 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:34 p.m.