Triple

T20895266
Position Surface form Disambiguated ID Type / Status
Subject Ajaigarh State E514515 entity
Predicate capital P234 FINISHED
Object Ajaigarh 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: Ajaigarh | Statement: [Ajaigarh State, capital, Ajaigarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ajaigarh
Context triple: [Ajaigarh State, capital, Ajaigarh]
  • A. Ajaigarh chosen
    Ajaigarh is a historic town in Madhya Pradesh, India, known for its hilltop fort and scenic location in the Vindhya ranges.
  • B. Narsinghgarh
    Narsinghgarh is a historic town in central India that once served as the administrative and cultural center of the former princely Narsinghgarh State.
  • C. Alirajpur
    Alirajpur is a town and district headquarters in western Madhya Pradesh, India, known for its predominantly tribal population and vibrant indigenous culture.
  • D. Bahadurgarh
    Bahadurgarh is a rapidly developing city in the Indian state of Haryana that forms part of the urban agglomeration surrounding Delhi.
  • E. Anupgarh
    Anupgarh is a town in the Ganganagar district of Rajasthan, India, known for its agricultural surroundings and proximity to the India–Pakistan 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_69e0b4f7ebe48190952a85547a0f31a1 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6d06233588190942493b709e30820 completed April 21, 2026, 1:18 a.m.
Created at: April 16, 2026, 12:47 p.m.