Triple

T23471104
Position Surface form Disambiguated ID Type / Status
Subject Sweetwater County, Wyoming E570128 entity
Predicate contains P35 FINISHED
Object Wamsutter, Wyoming
Wamsutter, Wyoming is a small town in southwestern Wyoming known historically as a railroad and natural gas industry community along Interstate 80.
E1593045 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: Wamsutter, Wyoming | Statement: [Sweetwater County, Wyoming, contains, Wamsutter, 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: Wamsutter, Wyoming
Triple: [Sweetwater County, Wyoming, contains, Wamsutter, Wyoming]
Generated description
Wamsutter, Wyoming is a small town in southwestern Wyoming known historically as a railroad and natural gas industry community along Interstate 80.

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_69e245af8a88819084f2704f6d265a92 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a6ff8dc0819086961b1f07030d9c completed April 29, 2026, 6:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f454bfe68819081e87c6dc6af4540 completed May 21, 2026, 5:47 p.m.
NEDg Description generation batch_6a0f46b69d288190b3fb6dcea9fb44b5 completed May 21, 2026, 5:53 p.m.
NED2 Entity disambiguation (via description) batch_6a0f47974f7c819088de0827ae15dd61 completed May 21, 2026, 5:57 p.m.
Created at: April 17, 2026, 5:55 p.m.