Triple

T20454720
Position Surface form Disambiguated ID Type / Status
Subject Ratargul Swamp Forest E501745 entity
Predicate locatedNear P294 FINISHED
Object Sylhet city 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: Sylhet city | Statement: [Ratargul Swamp Forest, locatedNear, Sylhet city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sylhet city
Context triple: [Ratargul Swamp Forest, locatedNear, Sylhet city]
  • 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. Narayanganj City
    Narayanganj City is a major industrial and river port city in central Bangladesh, known for its textile and jute industries and its proximity to the capital, Dhaka.
  • C. Sirajganj
    Sirajganj is a city in north-central Bangladesh known as a key river port and commercial hub on the banks of the Jamuna River.
  • D. Rangpur
    Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
  • E. Savar
    Savar is a suburban area near Dhaka in Bangladesh, known for its educational institutions, industrial zones, and historical significance.
  • 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e68d04ca4081909b428c31d16fca10 completed April 20, 2026, 8:31 p.m.
Created at: April 16, 2026, 11:32 a.m.