Triple

T2736078
Position Surface form Disambiguated ID Type / Status
Subject Whitefield E60633 entity
Predicate locatedIn P40 FINISHED
Object Bangalore 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: Bangalore | Statement: [Whitefield, locatedIn, Bangalore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangalore
Context triple: [Whitefield, locatedIn, Bangalore]
  • 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. Hyderabad
    Hyderabad is a major city in southern India known for its historic Charminar monument, rich Hyderabadi cuisine, and growing technology industry.
  • C. 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.
  • D. Mysuru
    Mysuru is a historic city in the southern Indian state of Karnataka, renowned for its royal heritage, palaces, and cultural festivals such as Dasara.
  • E. Bangalore Urban district
    Bangalore Urban district is a highly urbanized administrative district in the Indian state of Karnataka that encompasses the city of Bengaluru, a major technology and economic hub.
  • 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_69ab4b77febc819095603eb012cd141b completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb11c66c81909058f2978aa5fae9 completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6a37fdc8190bcdb33d7352d9e16 completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:56 p.m.