Triple

T20937670
Position Surface form Disambiguated ID Type / Status
Subject Chhatarpur State E515628 entity
Predicate hasBorderWith P224 FINISHED
Object Bijawar State 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: Bijawar State | Statement: [Chhatarpur State, hasBorderWith, Bijawar State]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bijawar State
Context triple: [Chhatarpur State, hasBorderWith, Bijawar State]
  • A. Bijawar State chosen
    Bijawar State was a former princely state in British India, located in the Bundelkhand region of present-day Madhya Pradesh.
  • B. Mundhar State
    Mundhar State was a small princely hill state located in the Simla Hills region of colonial India.
  • C. Rajpipla State
    Rajpipla State was a former princely state in British India, located in present-day Gujarat.
  • D. Bharana State
    Bharana State was a small princely state in colonial India that formed part of the group of minor hill principalities collectively known as the Simla Hill States.
  • E. Baraundha State
    Baraundha State was a former princely state in British India located in the Bagelkhand region, ruled by local royalty under indirect colonial administration.
  • 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_69e0b4fc13408190b06868df03c5c29b completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6f9534cd48190a86665fb1df6b077 completed April 21, 2026, 4:13 a.m.
Created at: April 16, 2026, 12:49 p.m.