Triple

T20171102
Position Surface form Disambiguated ID Type / Status
Subject Baran district E491959 entity
Predicate borderedBy P224 FINISHED
Object Kota district 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: Kota district | Statement: [Baran district, borderedBy, Kota district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kota district
Context triple: [Baran district, borderedBy, Kota district]
  • A. Kota district chosen
    Kota district is an administrative region in the southeastern part of Rajasthan, India, known for its industrial city of Kota and its prominence as a national hub for engineering and medical entrance exam coaching.
  • B. Buka District
    Buka District is an administrative district located within the Tashkent Region of Uzbekistan.
  • C. Gaya district
    Gaya district is an administrative region in the Indian state of Bihar, renowned as a major Buddhist pilgrimage center that includes the sacred site of Bodh Gaya.
  • D. Buyende District
    Buyende District is an administrative district in eastern Uganda, known for its rural communities and location along the shores of Lake Kyoga.
  • E. Saha District
    Saha District is an administrative district (gu) in the southwestern part of Busan, South Korea, known for its coastal areas and residential neighborhoods.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66848ae3c8190aa5fde66da35a89a completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.