Triple

T34080716
Position Surface form Disambiguated ID Type / Status
Subject L’Anse, Michigan E874032 entity
Predicate servedBy P82 FINISHED
Object Michigan State Highway 38
Michigan State Highway 38 is a former state trunkline highway in Michigan’s Upper Peninsula that once connected several communities, including L’Anse, across a rural, forested region.
E2080439 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: Michigan State Highway 38 | Statement: [L’Anse, Michigan, servedBy, Michigan State Highway 38]
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: Michigan State Highway 38
Triple: [L’Anse, Michigan, servedBy, Michigan State Highway 38]
Generated description
Michigan State Highway 38 is a former state trunkline highway in Michigan’s Upper Peninsula that once connected several communities, including L’Anse, across a rural, forested 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_69f349a61d448190b74642f325d3eb7a completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70c0605a48190b6edb215231be9f4 completed May 3, 2026, 8:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36ae5471f48190b664d46c2805b574 completed June 20, 2026, 3:14 p.m.
NEDg Description generation batch_6a36aed66c20819091ea25f3d7c531e9 completed June 20, 2026, 3:16 p.m.
NED2 Entity disambiguation (via description) batch_6a36af6a16688190bb1feb2a972f3945 completed June 20, 2026, 3:19 p.m.
Created at: May 1, 2026, 1:52 a.m.