Triple

T15630455
Position Surface form Disambiguated ID Type / Status
Subject Lodoselo E375796 entity
Predicate hasMunicipality P847 FINISHED
Object Sarreaus E1168839 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: Sarreaus | Statement: [Lodoselo, hasMunicipality, Sarreaus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarreaus
Context triple: [Lodoselo, hasMunicipality, Sarreaus]
  • A. Sarreaus chosen
    Sarreaus is a municipality in the province of Ourense, in the autonomous community of Galicia in northwestern Spain.
  • B. Sarrien
    Sarrien is a French surname most notably borne by Ferdinand Sarrien, a politician who served as Prime Minister of France in the early 20th century.
  • C. Saravena
    Saravena is a Colombian town and municipality located in the northeastern oil-producing and conflict-affected region near the border with Venezuela.
  • D. Sardoal
    Sardoal is a small Portuguese municipality known for its historic village center and traditional religious and cultural festivities, located in the Centro Region of Portugal.
  • E. Loelva
    Loelva is a river flowing through Norway’s scenic Loen valley, known for its glacial origins and striking turquoise waters.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04eb536348190b93ed3c178d1ffb8 completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff678c9d8c8190be73b6e7ed558e99 completed May 9, 2026, 4:57 p.m.
Created at: April 10, 2026, 4:14 a.m.