Triple

T20204673
Position Surface form Disambiguated ID Type / Status
Subject historical Georgian highlands E493317 entity
Predicate includesRegion P285 FINISHED
Object Mtiuleti 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: Mtiuleti | Statement: [historical Georgian highlands, includesRegion, Mtiuleti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mtiuleti
Context triple: [historical Georgian highlands, includesRegion, Mtiuleti]
  • A. Mtiuleti chosen
    Mtiuleti is a mountainous historical region in northeastern Georgia known for its rugged landscapes and traditional highland villages.
  • B. Lekutu
    Lekutu is a township in Fiji’s Bua Province on the island of Vanua Levu, serving as a local center for surrounding rural communities.
  • C. Motlatsi
    Motlatsi is a distinctive design style used in traditional Basotho blankets, recognized for its culturally symbolic patterns and motifs.
  • D. Umtata
    Umtata is the former name of Mthatha, a town in South Africa’s Eastern Cape that serves as a regional economic and administrative center.
  • E. Mkushi
    Mkushi is a farming and trading town in Zambia known for its commercial agriculture, particularly large-scale commercial farming.
  • 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d913c088190b80b251fba5c368f completed April 20, 2026, 6:16 p.m.
Created at: April 11, 2026, 11:38 p.m.