Triple

T2342263
Position Surface form Disambiguated ID Type / Status
Subject Arusha, Tanzania E45051 entity
Predicate locatedAtFootOf P7611 FINISHED
Object Mount Meru E197967 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 Meru | Statement: [Arusha, Tanzania, locatedAtFootOf, Mount Meru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Meru
Context triple: [Arusha, Tanzania, locatedAtFootOf, Mount Meru]
  • A. Mount Meru chosen
    Mount Meru is a dormant stratovolcano in northern Tanzania, renowned as one of Africa’s highest peaks and a prominent feature near Arusha and Mount Kilimanjaro.
  • B. Gigiri
    Gigiri is an affluent diplomatic and residential district in Nairobi, Kenya, known for hosting major international institutions and embassies.
  • C. Mount Heha
    Mount Heha is the tallest mountain in Burundi, located in the Burundi Highlands near the city of Bujumbura.
  • D. Maha Meru
    Maha Meru is the three-dimensional sacred geometric form of the Sri Yantra, revered in Hindu and Tantric traditions as a powerful representation of the cosmos and divine energy.
  • E. Mount Kawi
    Mount Kawi is a stratovolcano in East Java, Indonesia, known for its scenic highland landscapes and cultural significance to local 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_69a88917935081909b755dbf38e81024 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc6ad01fc81909e386986e9acc989 completed March 7, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae9622cdb08190835222482bd22cf4 completed March 9, 2026, 9:42 a.m.
Created at: March 4, 2026, 7:52 p.m.