Triple

T7152320
Position Surface form Disambiguated ID Type / Status
Subject Mount Mulanje E166720 entity
Predicate hasPlateau P3885 FINISHED
Object Chambe Plateau E646090 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: Chambe Plateau | Statement: [Mount Mulanje, hasPlateau, Chambe Plateau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chambe Plateau
Context triple: [Mount Mulanje, hasPlateau, Chambe Plateau]
  • A. Nkambe Plateau
    Nkambe Plateau is a highland area in northwestern Cameroon known for its elevated terrain, cooler climate, and predominantly rural, agricultural communities.
  • B. Batéké Plateau
    The Batéké Plateau is a highland region of savanna and ancient volcanic formations spanning parts of Gabon, the Republic of the Congo, and the Democratic Republic of the Congo in Central Africa.
  • C. Ufipa Plateau
    The Ufipa Plateau is a highland region in southwestern Tanzania known as the traditional homeland of the Fipa people.
  • D. Luye Plateau
    Luye Plateau is a scenic highland area in southeastern Taiwan renowned for its tea plantations, hot air balloon festivals, and panoramic views over Taitung’s rural landscape.
  • E. Lichenya Plateau chosen
    Lichenya Plateau is a high, expansive upland area on Malawi’s Mount Mulanje, known for its scenic grasslands, forests, and hiking routes.
  • 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_69c68886779c8190a8e3fbabffe68253 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e7f52c1081908c4fa424d5e965bc completed March 27, 2026, 8:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b8f42abc8190856210b8dea0a6de completed March 28, 2026, 11:18 a.m.
Created at: March 27, 2026, 2:46 p.m.