Triple

T28403183
Position Surface form Disambiguated ID Type / Status
Subject Coast of Death E719445 entity
Predicate hasNameInLanguage P15 FINISHED
Object Costa de la Muerte (Spanish)
Costa de la Muerte is a rugged, storm-battered stretch of coastline in Galicia, northwestern Spain, notorious for its dangerous waters and numerous shipwrecks.
 E1815991 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: Costa de la Muerte (Spanish) | Statement: [Coast of Death, hasNameInLanguage, Costa de la Muerte (Spanish)]
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: Costa de la Muerte (Spanish)
Triple: [Coast of Death, hasNameInLanguage, Costa de la Muerte (Spanish)]
Generated description
Costa de la Muerte is a rugged, storm-battered stretch of coastline in Galicia, northwestern Spain, notorious for its dangerous waters and numerous shipwrecks.

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_69eff6efd1b08190ae3cefd4f11388a2 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64d6e29388190a285f0ff5bc70a3f completed May 2, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16331010908190a8cb889688bb9e88 completed May 26, 2026, 11:56 p.m.
NEDg Description generation batch_6a1633b3404c81909756786e737b28a6 completed May 26, 2026, 11:58 p.m.
NED2 Entity disambiguation (via description) batch_6a1634fc4e648190932ce497c76e05d1 completed May 27, 2026, 12:04 a.m.
Created at: April 28, 2026, 1:21 a.m.