Triple

T28868482
Position Surface form Disambiguated ID Type / Status
Subject Kent Valley Loop Trails E729069 entity
Predicate primaryWaterBody P1489 FINISHED
Object Green River
The Green River is a significant river in Washington State that flows through the Kent Valley and supports local ecosystems, recreation, and regional water management.
 E187047 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 | Statement: [Kent Valley Loop Trails, primaryWaterBody, Green River]
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
Triple: [Kent Valley Loop Trails, primaryWaterBody, Green River]
Generated description
The Green River is a significant river in Washington State that flows through the Kent Valley and supports local ecosystems, recreation, and regional water management.

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_69f031a01cbc8190ba87270bb6fe4639 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65a439bf08190b1ee83d7bdba5b6b completed May 2, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260bf9ccac819080a82a9a5933ee96 completed June 8, 2026, 12:25 a.m.
NEDg Description generation batch_6a2611a7743c8190a62513eb4f3a1828 completed June 8, 2026, 12:49 a.m.
NED2 Entity disambiguation (via description) batch_6a261223305481909e0befe2eda8a9c1 completed June 8, 2026, 12:51 a.m.
Created at: April 28, 2026, 6:49 a.m.