Triple

T24665635
Position Surface form Disambiguated ID Type / Status
Subject Diamond Lake, Oregon E610666 entity
Predicate hasTrail P3625 FINISHED
Object Diamond Lake Loop Trail
Diamond Lake Loop Trail is a scenic multi-use path encircling Diamond Lake in southern Oregon, popular for hiking, biking, and lake views with close access to Mount Bailey and Mount Thielsen.
E1645882 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: Diamond Lake Loop Trail | Statement: [Diamond Lake, Oregon, hasTrail, Diamond Lake Loop 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: Diamond Lake Loop Trail
Triple: [Diamond Lake, Oregon, hasTrail, Diamond Lake Loop Trail]
Generated description
Diamond Lake Loop Trail is a scenic multi-use path encircling Diamond Lake in southern Oregon, popular for hiking, biking, and lake views with close access to Mount Bailey and Mount Thielsen.

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_69e2c4d505cc8190981881df06c0bf52 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40f9be2288190809cb33272b732c3 completed May 1, 2026, 2:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1004a2ba048190a88f4259295c24fc completed May 22, 2026, 7:24 a.m.
NEDg Description generation batch_6a1005b203048190bada1a7e9e78b1f5 completed May 22, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_6a10063001788190835d04b4e685ee64 completed May 22, 2026, 7:30 a.m.
Created at: April 18, 2026, 2:39 a.m.