Triple

T9740226
Position Surface form Disambiguated ID Type / Status
Subject MPC Film E236167 entity
Predicate hasOfficeIn P1268 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: [MPC Film, hasOfficeIn, Bangalore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangalore
Context triple: [MPC Film, hasOfficeIn, 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. Mambai
    Mambai is an Austronesian language spoken primarily in East Timor, where it is one of the country’s major indigenous languages.
  • 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. 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.
  • 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_69ca84d313e88190983ee6ffd0ef60d2 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f29a5bc8190b2b391017405c71e completed April 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1afe974608190874e2aba2189de80 completed April 5, 2026, 12:42 a.m.
Created at: March 30, 2026, 8:22 p.m.