Triple

T26857561
Position Surface form Disambiguated ID Type / Status
Subject Coronado Islands E676235 entity
Predicate hasIsland P970 FINISHED
Object Pilón de Azúcar
Pilón de Azúcar is a small, rocky islet within Mexico’s Coronado Islands archipelago off the coast of Baja California, known for its rugged terrain and surrounding marine life.
E1745924 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: Pilón de Azúcar | Statement: [Coronado Islands, hasIsland, Pilón de Azúcar]
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: Pilón de Azúcar
Triple: [Coronado Islands, hasIsland, Pilón de Azúcar]
Generated description
Pilón de Azúcar is a small, rocky islet within Mexico’s Coronado Islands archipelago off the coast of Baja California, known for its rugged terrain and surrounding marine life.

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_69eee9b9d7708190a15d7485709ae981 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61b98322881908adb98b258af26d5 completed May 2, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121355992c8190bc6e97895ab6241e completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a12176443cc8190ac9787c32fe3913c completed May 23, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_6a1217fa71b48190a1b9d88ae744fea6 completed May 23, 2026, 9:11 p.m.
Created at: April 27, 2026, 5:22 a.m.