Triple

T20218541
Position Surface form Disambiguated ID Type / Status
Subject Rajshahi Division E495189 entity
Predicate containsCity P294 FINISHED
Object Sirajganj NE NERFINISHED

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: Sirajganj | Statement: [Rajshahi Division, containsCity, Sirajganj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sirajganj
Context triple: [Rajshahi Division, containsCity, Sirajganj]
  • A. Sirajganj chosen
    Sirajganj is a city in north-central Bangladesh known as a key river port and commercial hub on the banks of the Jamuna River.
  • B. Faridpur
    Faridpur is a historic town in central Bangladesh known for its cultural heritage and role in the Bengal Renaissance.
  • C. Jamalpur
    Jamalpur is a city in central Bangladesh known as an important regional hub for agriculture and trade near the Jamuna River.
  • D. Chapainawabganj
    Chapainawabganj is a district town in western Bangladesh known for its mango production and location near the border with India.
  • E. Sahebganj
    Sahebganj is a town and district headquarters in the eastern Indian state of Jharkhand, known for its location along the Ganges River and its role as an administrative and commercial center in the region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66edaeeb08190bb74bd4a10aceca2 completed April 20, 2026, 6:22 p.m.
Created at: April 11, 2026, 11:39 p.m.