Triple

T4304041
Position Surface form Disambiguated ID Type / Status
Subject Dara Shikoh E99910 entity
Predicate birthPlace P1 FINISHED
Object Ajmer E8458 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: Ajmer | Statement: [Dara Shikoh, birthPlace, Ajmer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ajmer
Context triple: [Dara Shikoh, birthPlace, Ajmer]
  • A. Bikaner
    Bikaner is a historic city in the Indian state of Rajasthan, known for its desert landscape, grand forts, and rich Rajasthani culture.
  • B. Jodhpur
    Jodhpur is a historic city in the Indian state of Rajasthan, renowned for its blue-painted old town, imposing Mehrangarh Fort, and role as a major cultural and commercial center on the edge of the Thar Desert.
  • C. Marwar
    Marwar is a historic desert region in the western part of Rajasthan, India, known for its Rajput heritage, forts, and distinctive Marwari culture and language.
  • D. Ajmer-Merwara chosen
    Ajmer-Merwara was a small British Indian province centered on the city of Ajmer in present-day Rajasthan, administered directly by the colonial government rather than through local princely rulers.
  • E. Bhilwara
    Bhilwara is a prominent industrial city in the Indian state of Rajasthan, known especially for its large textile and garment manufacturing sector.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350b792608190ac778b79c740256a completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e4ebb3808190a4be632e36140648 completed March 14, 2026, 10:44 p.m.
Created at: March 12, 2026, 11:09 p.m.