Triple

T14876603
Position Surface form Disambiguated ID Type / Status
Subject Sania Mirza E349883 entity
Predicate placeOfBirth P1 FINISHED
Object Maharashtra E19223 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: Maharashtra | Statement: [Sania Mirza, placeOfBirth, Maharashtra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maharashtra
Context triple: [Sania Mirza, placeOfBirth, Maharashtra]
  • A. Maharashtra chosen
    Maharashtra is a large and economically significant state in western India, known for its capital Mumbai, the country’s financial hub, and its rich cultural and historical heritage.
  • B. Maharashtri
    Maharashtri is an ancient Middle Indo-Aryan language, a major literary Prakrit historically used in parts of western and central India.
  • C. Gujarat
    Gujarat is a western coastal state of India known for its significant role in trade and industry, rich cultural heritage, and historic cities such as Ahmedabad.
  • D. Maharashtra and Gujarat
    Maharashtra and Gujarat are neighboring states in western India known for their major economic hubs, diverse cultures, and long Arabian Sea coastlines.
  • E. Marathwada
    Marathwada is a historically significant and predominantly rural region in central Maharashtra, India, known for its drought-prone agriculture, cultural heritage, and cities like Aurangabad.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e4e4448190a8796573bc6d1069 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e8192548190ad268b5804c97060 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 1:55 a.m.