Triple

T4142765
Position Surface form Disambiguated ID Type / Status
Subject Santos E89307 entity
Predicate locatedNear P294 FINISHED
Object São Vicente E293520 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: São Vicente | Statement: [Santos, locatedNear, São Vicente]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: São Vicente
Context triple: [Santos, locatedNear, São Vicente]
  • A. São Vicente
    São Vicente is a prominent island in Cape Verde known for its cultural hub Mindelo, vibrant music scene, and important Atlantic port.
  • B. São Vicente chosen
    São Vicente is a coastal Brazilian city in the state of São Paulo, recognized as one of the country’s oldest European-founded settlements.
  • C. Santa Cruz do Sul
    Santa Cruz do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage, architecture, and traditions.
  • D. Boa Vista
    Boa Vista is a central neighborhood in Recife, Brazil, known for its historic architecture, commercial activity, and cultural significance.
  • E. Boa Vista
    Boa Vista is one of Cape Verde’s easternmost islands, known for its extensive sandy beaches, desert-like landscapes, and tourism-focused resorts.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af024cc7e88190b23b39d6f5f2a2e0 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576cff6c881909134804ba6f9876d completed March 14, 2026, 2:55 p.m.
Created at: March 9, 2026, 3:43 p.m.