Triple

T27473166
Position Surface form Disambiguated ID Type / Status
Subject Cíes Islands E693374 entity
Predicate hasBeach P1922 FINISHED
Object Praia de San Martiño
Praia de San Martiño is a secluded, pristine beach on the Cíes Islands off the coast of Galicia in northwestern Spain, known for its clear waters and unspoiled natural setting.
E1778303 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: Praia de San Martiño | Statement: [Cíes Islands, hasBeach, Praia de San Martiño]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Praia de San Martiño
Triple: [Cíes Islands, hasBeach, Praia de San Martiño]
Generated description
Praia de San Martiño is a secluded, pristine beach on the Cíes Islands off the coast of Galicia in northwestern Spain, known for its clear waters and unspoiled natural setting.

Provenance (5 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_69ef538105548190a771cc5a0cf8c211 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62e422e7c8190a256e3155a22ba27 completed May 2, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12c5a07bf88190855441e474154b1a completed May 24, 2026, 9:32 a.m.
NEDg Description generation batch_6a12c6b232108190a185cccf8206578f completed May 24, 2026, 9:36 a.m.
NED2 Entity disambiguation (via description) batch_6a12c74f073c8190b84c1e5acc666bf3 completed May 24, 2026, 9:39 a.m.
Created at: April 27, 2026, 12:55 p.m.