Triple

T14518012
Position Surface form Disambiguated ID Type / Status
Subject Nadaprabhu Kempegowda Metro Station E340574 entity
Predicate cityServed P82 FINISHED
Object Bengaluru 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 | Statement: [Nadaprabhu Kempegowda Metro Station, cityServed, Bengaluru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bengaluru
Context triple: [Nadaprabhu Kempegowda Metro Station, cityServed, Bengaluru]
  • 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. Indiranagar
    Indiranagar is a prominent residential and commercial neighborhood in eastern Bengaluru, known for its upscale eateries, pubs, and shopping streets.
  • C. Mambai
    Mambai is an Austronesian language spoken primarily in East Timor, where it is one of the country’s major indigenous languages.
  • D. Hyderabad
    Hyderabad is a major city in southern India known for its historic Charminar monument, rich Hyderabadi cuisine, and growing technology industry.
  • E. 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.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a6f50208190b687b505f5cd1aa2 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a420040819097ee73390d625338 completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:22 a.m.