Triple

T24410440
Position Surface form Disambiguated ID Type / Status
Subject Sucia Island Marine State Park E615432 entity
Predicate locatedOn P40 FINISHED
Object Sucia Island
Sucia Island is a small, scenic island in Washington State’s San Juan Islands, known for its protected coves, marine life, and popular boating and camping opportunities.
E2292819 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: Sucia Island | Statement: [Sucia Island Marine State Park, locatedOn, Sucia Island]
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: Sucia Island
Triple: [Sucia Island Marine State Park, locatedOn, Sucia Island]
Generated description
Sucia Island is a small, scenic island in Washington State’s San Juan Islands, known for its protected coves, marine life, and popular boating and camping opportunities.

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_69e2d7e9bfac8190a748952a90957106 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f2958138388190937a5e3ed6346e09 completed April 29, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a2dd0c4788190ab76dc0b3b8e6179 completed Aug. 10, 2026, 8 p.m.
NEDg Description generation batch_6a7a2e35bb9481908551c87cab4e68fd completed Aug. 10, 2026, 8:01 p.m.
NED2 Entity disambiguation (via description) batch_6a7a2ec7fd5c8190a8773f2ec352cdfa completed Aug. 10, 2026, 8:04 p.m.
Created at: April 18, 2026, 2:06 a.m.