Triple

T16893571
Position Surface form Disambiguated ID Type / Status
Subject Îles du Salut E424237 entity
Predicate locatedNear P294 FINISHED
Object Kourou E155694 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: Kourou | Statement: [Îles du Salut, locatedNear, Kourou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kourou
Context triple: [Îles du Salut, locatedNear, Kourou]
  • A. Kourou chosen
    Kourou is a coastal town in French Guiana best known as the site of the Guiana Space Centre, a major European spaceport.
  • B. Guiana Space Centre
    The Guiana Space Centre is a major European spaceport located in French Guiana, used for launching a wide range of commercial and scientific missions including flagship observatories.
  • C. Baikonur
    Baikonur is a town in Kazakhstan historically associated with the Soviet and Russian space programs, giving its name to the nearby Baikonur Cosmodrome.
  • D. Baikonur
    Baikonur is a metro station on the Almaty Metro system in Almaty, Kazakhstan.
  • E. Cidade do Maio
    Cidade do Maio is the main urban center and administrative capital of Maio Island in Cape Verde, known for its coastal setting and role as the island’s political and economic hub.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc6b97c8190b18aca477d6ef647 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7aa83bc8190832d2f3903ce0081 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:29 a.m.