Triple

T677321
Position Surface form Disambiguated ID Type / Status
Subject Saint Lucia E13106 entity
Predicate largestCity P235 FINISHED
Object Castries E83411 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: Castries | Statement: [Saint Lucia, largestCity, Castries]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Castries
Context triple: [Saint Lucia, largestCity, Castries]
  • A. Castries chosen
    Castries is the largest city and main commercial and cultural center of Saint Lucia in the eastern Caribbean.
  • B. Bridgetown
    Bridgetown is the largest city and main commercial and cultural center of Barbados, located on the island’s southwestern coast.
  • C. Bequia
    Bequia is a small, picturesque Caribbean island known for its beaches, sailing culture, and laid-back atmosphere, located in the Grenadines island chain.
  • D. Port-au-Prince
    Port-au-Prince is the capital and largest city of Haiti, serving as the country’s political, economic, and cultural center.
  • E. Francistown
    Francistown is a major city in northeastern Botswana, historically known as a gold-mining center and an important commercial hub near the border with Zimbabwe.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a04c89148190b6330e86697bb37b completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc9f5f7c8190a766c6b545d1abd8 completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:36 p.m.