Triple

T6973080
Position Surface form Disambiguated ID Type / Status
Subject Wipro Limited E161643 entity
Predicate headquartersLocation P62 FINISHED
Object Bengaluru, India E12663 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: Bengaluru, India | Statement: [Wipro Limited, headquartersLocation, Bengaluru, India]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bengaluru, India
Context triple: [Wipro Limited, headquartersLocation, Bengaluru, India]
  • A. Bengaluru chosen
    Bengaluru is a major Indian metropolis known as the country’s leading technology and innovation hub, often called the “Silicon Valley of India.”
  • B. New Delhi, India
    New Delhi, India is the capital city of India, serving as the nation’s political and administrative center and home to key government institutions and historic landmarks.
  • C. Hyderabad
    Hyderabad is a major city in southern India known for its historic Charminar monument, rich Hyderabadi cuisine, and growing technology industry.
  • D. Hyderabad
    Hyderabad is a major city in the Sindh province of Pakistan, known for its historical significance, vibrant culture, and role as an important commercial and industrial center.
  • E. Manipal
    Manipal is a university town in Karnataka, India, known for its large private educational institutions and vibrant student community.
  • 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_69c68854a0d88190bc0bf82263f1afce completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db3aad108190b19df2d21f5ce168 completed March 27, 2026, 7:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c794318fb08190a9a89570b2a6999b completed March 28, 2026, 8:41 a.m.
Created at: March 27, 2026, 2:30 p.m.