Triple

T22208402
Position Surface form Disambiguated ID Type / Status
Subject Ashoknagar district E548875 entity
Predicate hasTown P847 FINISHED
Object Chanderi 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: Chanderi | Statement: [Ashoknagar district, hasTown, Chanderi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chanderi
Context triple: [Ashoknagar district, hasTown, Chanderi]
  • A. Chanderi chosen
    Chanderi is a historic town in central India renowned for its medieval architecture and its traditional handwoven Chanderi silk and cotton textiles.
  • B. Beawar
    Beawar is a prominent commercial and industrial town in Rajasthan, India, known historically as a major trading center in the region.
  • C. Jhansi
    Jhansi is a historic city in northern India, renowned for its strategic fort and its central role in the 1857 uprising against British colonial rule.
  • D. Chittorgarh
    Chittorgarh is a historic city in Rajasthan, India, renowned for its massive hilltop fort, tales of Rajput valor, and rich cultural traditions.
  • E. Bhilsa
    Bhilsa is a historical town in the Vidisha district of Madhya Pradesh, India, known for its ancient Buddhist and Hindu archaeological sites.
  • 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_69e11e3f7e04819089806d81d5ac431e completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b29eb808190ab8abaa1e0e354fa completed April 28, 2026, 9:48 p.m.
Created at: April 16, 2026, 8:36 p.m.