Triple

T25867684
Position Surface form Disambiguated ID Type / Status
Subject Carbon County, Wyoming E651662 entity
Predicate contains P35 FINISHED
Object Riverside, Wyoming
Riverside, Wyoming is a small town in south-central Wyoming known for its rural setting and proximity to outdoor recreation in the Medicine Bow–Routt National Forest region.
E1719552 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: Riverside, Wyoming | Statement: [Carbon County, Wyoming, contains, Riverside, Wyoming]
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: Riverside, Wyoming
Triple: [Carbon County, Wyoming, contains, Riverside, Wyoming]
Generated description
Riverside, Wyoming is a small town in south-central Wyoming known for its rural setting and proximity to outdoor recreation in the Medicine Bow–Routt National Forest region.

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_69e7ab3a199c81909227cb964cacfe24 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f602d9b5c8819093aebab7bb20044d completed May 2, 2026, 1:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118f87799c8190819ce404acd7da3e completed May 23, 2026, 11:29 a.m.
NEDg Description generation batch_6a119053e3b0819092c8e62b5b4ae02a completed May 23, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_6a1190db5ab48190a5b902fee03abdde completed May 23, 2026, 11:34 a.m.
Created at: April 22, 2026, 8:07 a.m.