Triple

T16887533
Position Surface form Disambiguated ID Type / Status
Subject Asianet E421576 entity
Predicate secondaryOfficeLocation P7992 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: [Asianet, secondaryOfficeLocation, Bengaluru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bengaluru
Context triple: [Asianet, secondaryOfficeLocation, 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. Bengaluru Metropolitan Region
    Bengaluru Metropolitan Region is the large urban agglomeration centered on Bengaluru city in Karnataka, India, encompassing its surrounding suburbs, satellite towns, and industrial areas under a unified planning and development framework.
  • C. Indiranagar
    Indiranagar is a prominent residential and commercial neighborhood in eastern Bengaluru, known for its upscale eateries, pubs, and shopping streets.
  • D. Mambai
    Mambai is an Austronesian language spoken primarily in East Timor, where it is one of the country’s major indigenous languages.
  • E. Hyderabad
    Hyderabad is a major city in southern India known for its historic Charminar monument, rich Hyderabadi cuisine, and growing technology industry.
  • 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc1f42481909dcf595358c23497 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7a61c608190909a462e9e77220b completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:29 a.m.