Triple

T19030311
Position Surface form Disambiguated ID Type / Status
Subject Raja of Kadiri E465717 entity
Predicate hasCapital P204 FINISHED
Object Dahanapura 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: Dahanapura | Statement: [Raja of Kadiri, hasCapital, Dahanapura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dahanapura
Context triple: [Raja of Kadiri, hasCapital, Dahanapura]
  • A. Dahanapura chosen
    Dahanapura was the principal city and political center of the historical Kediri Kingdom in Java.
  • B. Dantapura
    Dantapura was an ancient city traditionally identified as the royal and administrative center of the Kalinga kingdom in eastern India.
  • C. Mahadevapura
    Mahadevapura is a rapidly developing residential and commercial neighborhood in eastern Bengaluru, India, known for its proximity to major IT parks and tech hubs.
  • D. Pravarapura
    Pravarapura was an ancient city in central India that served as a major political and cultural center under the Vakataka dynasty.
  • E. Valmikinagar
    Valmikinagar is a town in Bihar, India, known for its proximity to the Valmiki Tiger Reserve and its location along the Gandak River near the Indo-Nepal border.
  • 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_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d73f98dc81909acbb366f00d2d54 completed April 20, 2026, 7:35 a.m.
Created at: April 10, 2026, 12:02 p.m.