Triple

T17979933
Position Surface form Disambiguated ID Type / Status
Subject Mount Kailasa region E449573 entity
Predicate accessPoint P1985 FINISHED
Object Darchen NE NERFINISHED

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: Darchen | Statement: [Mount Kailasa region, accessPoint, Darchen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darchen
Context triple: [Mount Kailasa region, accessPoint, Darchen]
  • A. Darchen chosen
    Darchen is a small Tibetan settlement that serves as the main starting point and base for pilgrimages and treks around Mount Kailash and Lake Manasarovar.
  • B. Darchula
    Darchula is a remote mountainous district in far-western Nepal known for its rugged Himalayan terrain, border with India and China, and culturally diverse communities.
  • C. Marpha
    Marpha is a picturesque Thakali village in Nepal’s Mustang region, known for its traditional stone houses, apple orchards, and role as a popular stop on the Annapurna Circuit trekking route.
  • D. Dhala
    Dhala is a town and district in southwestern Yemen, historically part of the British-era protectorate structures that later formed the Federation of South Arabia.
  • E. Lhuentse
    Lhuentse is a small town in northeastern Bhutan known for its traditional Bhutanese architecture, rich cultural heritage, and production of fine handwoven textiles.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b202aab88190b44851808c75a848 completed April 19, 2026, 10:44 a.m.
Created at: April 10, 2026, 10:22 a.m.