Triple

T27710585
Position Surface form Disambiguated ID Type / Status
Subject Wisconsin State Highway 16 E698664 entity
Predicate hasRouteDesignation P5539 FINISHED
Object WIS 16
WIS 16 is a state highway in Wisconsin that runs east–west across the state, connecting several major cities and serving as an important regional transportation route.
 E1785686 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: WIS 16 | Statement: [Wisconsin State Highway 16, hasRouteDesignation, WIS 16]
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: WIS 16
Triple: [Wisconsin State Highway 16, hasRouteDesignation, WIS 16]
Generated description
WIS 16 is a state highway in Wisconsin that runs east–west across the state, connecting several major cities and serving as an important regional transportation route.

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_69ef590f655c81909f93893b3b3219b2 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f635cb7bfc81908bc5f45e6ab36aae completed May 2, 2026, 5:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e4615da081908cd4c790e4363e61 completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e51506ac8190bc8cac0bad87dad5 completed May 24, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a12e5e1eafc8190912e291b91690548 completed May 24, 2026, 11:49 a.m.
Created at: April 27, 2026, 3:02 p.m.