Triple

T8654285
Position Surface form Disambiguated ID Type / Status
Subject Jangipur E205375 entity
Predicate locatedIn P40 FINISHED
Object Murshidabad district E66134 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: Murshidabad district | Statement: [Jangipur, locatedIn, Murshidabad district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murshidabad district
Context triple: [Jangipur, locatedIn, Murshidabad district]
  • A. Murshidabad chosen
    Murshidabad is a historic city in West Bengal, India, that served as the capital of the Nawabs of Bengal and a major political and commercial center during the Mughal and early British periods.
  • B. Shatkhira District
    Shatkhira District is a southwestern district of Bangladesh known for its proximity to the Sundarbans mangrove forest and its location along the border with India.
  • C. Narsingdi District
    Narsingdi District is an administrative region in central Bangladesh known for its agriculture, textile industries, and proximity to the capital, Dhaka.
  • D. Bardhaman district
    Bardhaman district is a historically significant administrative region in the Indian state of West Bengal, known for its rich cultural heritage, agriculture, and coal-based industrial development.
  • E. Narayanganj District
    Narayanganj District is an industrially important and densely populated district in central Bangladesh, known especially for its textile and jute industries and its proximity to the capital, Dhaka.
  • 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_69ca8350897c819086cde7596fbe5fe7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc48432568819093b9a867b4f62b78 completed March 31, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef373a22c8190931b4107c68e7017 completed April 2, 2026, 10:53 p.m.
Created at: March 30, 2026, 6:29 p.m.