Triple

T27226191
Position Surface form Disambiguated ID Type / Status
Subject King County Regional Trail System E682018 entity
Predicate hasComponent P35 FINISHED
Object Green River Trail
The Green River Trail is a multi-use recreational path in King County, Washington, that follows the Green River through parks, neighborhoods, and industrial areas, providing scenic routes for walking, running, and cycling.
E1762497 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: Green River Trail | Statement: [King County Regional Trail System, hasComponent, Green River Trail]
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: Green River Trail
Triple: [King County Regional Trail System, hasComponent, Green River Trail]
Generated description
The Green River Trail is a multi-use recreational path in King County, Washington, that follows the Green River through parks, neighborhoods, and industrial areas, providing scenic routes for walking, running, and cycling.

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_69eefacdad7881908b7bca61c90a1a1e completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6264b0bbc8190aca2e1fb1ae773fd completed May 2, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12626e884c819092986b7623d9ac27 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a1263a80d848190ac06c46e255e9b26 completed May 24, 2026, 2:34 a.m.
NED2 Entity disambiguation (via description) batch_6a126448a36c8190837c7ea378f68cd3 completed May 24, 2026, 2:36 a.m.
Created at: April 27, 2026, 9:44 a.m.