Triple

T236787
Position Surface form Disambiguated ID Type / Status
Subject Bengal E4840 entity
Predicate majorCity P316 FINISHED
Object Dhaka E26021 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: Dhaka | Statement: [Bengal, majorCity, Dhaka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dhaka
Context triple: [Bengal, majorCity, Dhaka]
  • A. Dhaka chosen
    Dhaka is the capital and largest city of Bangladesh, serving as the country’s political, economic, and cultural center.
  • B. Calcutta
    Calcutta, now known as Kolkata, is a major cultural and commercial metropolis in eastern India that served as the capital of British India until the early 20th century.
  • C. Guwahati
    Guwahati is a major city in northeastern India, serving as a key cultural, economic, and transportation hub for the region.
  • D. Karachi
    Karachi is Pakistan’s sprawling economic hub and major port city on the Arabian Sea, known for its diverse population and central role in the country’s finance, industry, and culture.
  • E. Islamabad
    Islamabad is Pakistan’s planned, modern capital city known for its high standard of living, greenery, and role as the country’s political and administrative center.
  • 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_69a257c3d0708190b0871c4269d273e6 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25ccc5d548190b505bf1d99db41bd completed Feb. 28, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3695ec8cc8190a070462cd0022f6a completed Feb. 28, 2026, 10:17 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.