Triple

T5724314
Position Surface form Disambiguated ID Type / Status
Subject Hansa Mehta E126224 entity
Predicate placeOfDeath P21 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: [Hansa Mehta, placeOfDeath, Maharashtra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maharashtra
Context triple: [Hansa Mehta, placeOfDeath, 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_69c0082f723881908ce8bb13a0c0f8b7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02506d8288190b33bede6c22af773 completed March 22, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c059c9a99881909863a0d1b061df72 completed March 22, 2026, 9:06 p.m.
Created at: March 22, 2026, 3:47 p.m.