Triple

T13175253
Position Surface form Disambiguated ID Type / Status
Subject Nalón E313081 entity
Predicate passesNear P416 FINISHED
Object Langreo E701737 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: Langreo | Statement: [Nalón, passesNear, Langreo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Langreo
Context triple: [Nalón, passesNear, Langreo]
  • A. Langreo chosen
    Langreo is a town in Asturias, Spain, known in football for being one of the early youth clubs of striker David Villa.
  • B. Salen
    Salen is a small coastal village on the Isle of Mull in Scotland, known as a local hub with basic services for residents and visitors exploring the island.
  • C. Scalea
    Scalea is a coastal town and popular seaside resort in southern Italy’s Calabria region, known for its historic old center and beaches along the Tyrrhenian Sea.
  • D. Berjallien
    A Berjallien is a resident or native of Bourgoin-Jallieu, a town in the Isère department of southeastern France.
  • E. Namora
    Namora is a Marvel Comics character, often depicted as a powerful Atlantean-human hybrid and cousin of Namor, known for her superhuman strength, aquatic abilities, and role in undersea kingdoms.
  • 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_69d806ac3ee081909b2fd27d060aa974 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c303e3c819086cf0f0b6d9e61ca completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eafe03c48190992df41f77fb043e completed May 3, 2026, 6:28 a.m.
Created at: April 9, 2026, 9:14 p.m.