Triple

T13216463
Position Surface form Disambiguated ID Type / Status
Subject Marwari language E314628 entity
Predicate hasDialect P4251 FINISHED
Object Bikaneri E35816 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: Bikaneri | Statement: [Marwari language, hasDialect, Bikaneri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bikaneri
Context triple: [Marwari language, hasDialect, Bikaneri]
  • A. Sanganer
    Sanganer is a suburban town near Jaipur in Rajasthan, India, known for its traditional hand block printing, handmade paper industry, and historic Jain temples.
  • B. Bijbehara
    Bijbehara is a historic town in the Kashmir Valley of Jammu and Kashmir, India, known for its apple orchards and scenic location along the Jhelum River.
  • C. Ratangarh
    Ratangarh is a town in the Churu district of Rajasthan, India, known for its historic havelis and traditional Rajasthani architecture.
  • D. Bikaner chosen
    Bikaner is a historic city in the Indian state of Rajasthan, known for its desert landscape, grand forts, and rich Rajasthani culture.
  • E. Alwar
    Alwar is a historic city in northern India known for its forts, palaces, and proximity to the Sariska Tiger Reserve.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf28c9c819080d7b42d20f579d1 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff1ebf648190a27d11b3dc494446 completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:18 p.m.