Triple

T3696400
Position Surface form Disambiguated ID Type / Status
Subject Mawenzi E78468 entity
Predicate mapLabel P13793 FINISHED
Object Mawenzi Peak E78468 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: Mawenzi Peak | Statement: [Mawenzi, mapLabel, Mawenzi Peak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mawenzi Peak
Context triple: [Mawenzi, mapLabel, Mawenzi Peak]
  • A. Mawenzi chosen
    Mawenzi is the jagged, eroded eastern peak of Mount Kilimanjaro and one of its three main volcanic cones.
  • B. Uhuru Peak
    Uhuru Peak is the highest summit of Mount Kilimanjaro and the tallest point in Africa, renowned as a major goal for trekkers and climbers worldwide.
  • C. Mount Mutombo
    Mount Mutombo is the famous nickname of Hall of Fame NBA center Dikembe Mutombo, reflecting his towering height and dominant defensive presence on the basketball court.
  • D. Mount Kenya
    Mount Kenya is an extinct stratovolcano in central Kenya and Africa’s second-highest mountain, renowned for its rugged peaks, glaciers, and alpine ecosystems.
  • E. Mount Nyangani
    Mount Nyangani is a prominent mountain in eastern Zimbabwe known for its scenic highland landscapes and status as a popular hiking destination.
  • 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_69ad85e3b1888190abc983e06968696d completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc50f9ad88190a926042fa73d65dc completed March 8, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5120d23f481908f71e291c089505c completed March 14, 2026, 7:45 a.m.
Created at: March 8, 2026, 3:26 p.m.