Triple

T37669571
Position Surface form Disambiguated ID Type / Status
Subject Monroe County, Wisconsin E937917 entity
Predicate traversedBy P225 FINISHED
Object Wisconsin Highway 71
Wisconsin Highway 71 is a state highway in Wisconsin that runs east–west through several counties in the western part of the state, connecting small rural communities and local highways.
E2256966 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: Wisconsin Highway 71 | Statement: [Monroe County, Wisconsin, traversedBy, Wisconsin Highway 71]
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: Wisconsin Highway 71
Triple: [Monroe County, Wisconsin, traversedBy, Wisconsin Highway 71]
Generated description
Wisconsin Highway 71 is a state highway in Wisconsin that runs east–west through several counties in the western part of the state, connecting small rural communities and local highways.

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_69f76ed6df7c8190b018e5baea716ceb completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba9e4824081909b69a5d10c876529 completed May 6, 2026, 8:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4167f11ca481908c659e0878583e65 completed June 28, 2026, 6:29 p.m.
NEDg Description generation batch_6a416bb629348190a74da4c807a84aab completed June 28, 2026, 6:45 p.m.
NED2 Entity disambiguation (via description) batch_6a416c59fe448190bfe6cffcc42685a9 completed June 28, 2026, 6:47 p.m.
Created at: May 3, 2026, 4:18 p.m.