Triple

T12847366
Position Surface form Disambiguated ID Type / Status
Subject Seoni district E307214 entity
Predicate borderedBy P224 FINISHED
Object Mandla district E307213 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: Mandla district | Statement: [Seoni district, borderedBy, Mandla district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mandla district
Context triple: [Seoni district, borderedBy, Mandla district]
  • A. Mandla district chosen
    Mandla district is an administrative district in the central Indian state of Madhya Pradesh, known for its forested landscapes, tribal population, and proximity to Kanha National Park.
  • B. Kgatleng District
    Kgatleng District is an administrative region in southeastern Botswana known for its rural villages and proximity to the capital, Gaborone.
  • C. Insiza District
    Insiza District is a rural administrative district in Zimbabwe’s Matabeleland South Province, known for its mining and agricultural activities.
  • D. Pang Mapha District
    Pang Mapha District is a rural, mountainous district in northern Thailand known for its caves, karst landscapes, and ethnic minority communities.
  • E. Samtse District
    Samtse District is an administrative district in southwestern Bhutan known for its subtropical climate, agricultural production, and location along the border with India.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff49efc8190bd6bbac510cc4705 completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a549fc188190a7dfcf16faa5e415 completed May 3, 2026, 1:30 a.m.
Created at: April 9, 2026, 5:36 p.m.