Triple

T626230
Position Surface form Disambiguated ID Type / Status
Subject Dominica E15825 entity
Predicate largestCity P235 FINISHED
Object Roseau E78397 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: Roseau | Statement: [Dominica, largestCity, Roseau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roseau
Context triple: [Dominica, largestCity, Roseau]
  • A. Roseau chosen
    Roseau is the largest city and main commercial and administrative center of the Caribbean island nation of Dominica.
  • B. Monrovia
    Monrovia is the largest city and main economic and administrative center of Liberia, located on the Atlantic coast in West Africa.
  • C. Port-au-Prince
    Port-au-Prince is the capital and largest city of Haiti, serving as the country’s political, economic, and cultural center.
  • D. Port Louis
    Port Louis is the capital and largest city of Mauritius, serving as its main economic, political, and cultural center as well as a key regional port in the Indian Ocean.
  • E. Port of Spain
    Port of Spain is the capital city and main commercial and cultural center of Trinidad and Tobago, located on the northwest coast of the island of Trinidad.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e587c448190987943a6aad209d1 completed March 1, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a56935ec748190984b9cb6add6b700 completed March 2, 2026, 10:40 a.m.
Created at: March 1, 2026, 7:35 p.m.