Triple

T8405766
Position Surface form Disambiguated ID Type / Status
Subject Sonargaon E198493 entity
Predicate hasAlternativeName P39 FINISHED
Object Sonargaon City E198493 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: Sonargaon City | Statement: [Sonargaon, hasAlternativeName, Sonargaon City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sonargaon City
Context triple: [Sonargaon, hasAlternativeName, Sonargaon City]
  • A. Sonargaon chosen
    Sonargaon is a historic city in present-day Bangladesh that served as a major political and commercial center in medieval Bengal, renowned for its role in regional trade and Islamic culture.
  • 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. Mohiuddinnagar
    Mohiuddinnagar is a town in the Indian state of Bihar, situated within the Samastipur district.
  • D. Agargaon
    Agargaon is a prominent residential and administrative neighborhood in Dhaka, Bangladesh, known for housing several government offices and institutions.
  • 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 (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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb8312941c8190af0b2def0a4e02be completed March 31, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce02f8596c8190a61b6f1ffd5a609c completed April 2, 2026, 5:47 a.m.
Created at: March 30, 2026, 6:05 p.m.