Triple

T2072764
Position Surface form Disambiguated ID Type / Status
Subject St Albans, Hertfordshire E44851 entity
Predicate hasTwinTown P919 FINISHED
Object Sylhet E117161 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: Sylhet | Statement: [St Albans, Hertfordshire, hasTwinTown, Sylhet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylhet
Context triple: [St Albans, Hertfordshire, hasTwinTown, Sylhet]
  • A. Sylhet chosen
    Sylhet is a historically and culturally significant city and region in northeastern Bangladesh, known for its tea gardens, lush landscapes, and role as a major economic and spiritual center.
  • B. Barisal
    Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
  • C. Mymensingh
    Mymensingh is a historic city and district in central Bangladesh, known as an important administrative, educational, and cultural center along the Brahmaputra River.
  • D. Rajshahi
    Rajshahi is a prominent city in western Bangladesh, known as an important cultural, educational, and commercial center of the Bengal region.
  • E. Noakhali
    Noakhali is a coastal district in southeastern Bangladesh, historically part of the Bengal region and known for its agrarian economy and vulnerability to cyclones and river erosion.
  • 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_69a88916c2b48190a5ca2e9b12cad3ed completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba0eaa5081908f6d6ff80f79b1c9 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae272ee27c8190a4bb4690961dccf6 completed March 9, 2026, 1:49 a.m.
Created at: March 4, 2026, 7:41 p.m.