Triple

T3177148
Position Surface form Disambiguated ID Type / Status
Subject Governor of Bombay E66490 entity
Predicate seat P75 FINISHED
Object Bombay E9753 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: Bombay | Statement: [Governor of Bombay, seat, Bombay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bombay
Context triple: [Governor of Bombay, seat, Bombay]
  • A. Mumbai chosen
    Mumbai is a densely populated coastal metropolis in western India that serves as the country’s financial hub and the center of its film industry, Bollywood.
  • B. Calcutta
    Calcutta, now known as Kolkata, is a major cultural and commercial metropolis in eastern India that served as the capital of British India until the early 20th century.
  • C. Ahmedabad
    Ahmedabad is a major city in the western Indian state of Gujarat, known for its rich history, textile industry, and role as an important economic and cultural center.
  • D. Delhi
    Delhi is a major metropolitan region and the capital territory of India, known for its political significance, rich history, and diverse culture.
  • E. Pune
    Pune is a major cultural, educational, and IT hub in the western Indian state of Maharashtra, known for its universities, historical significance, and rapidly growing urban economy.
  • 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_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada69c2edc81908bfd23a1d5ce970e completed March 8, 2026, 4:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b324ea81f4819080e836dccf8254d0 completed March 12, 2026, 8:41 p.m.
Created at: March 8, 2026, 3:06 p.m.