Triple

T28763149
Position Surface form Disambiguated ID Type / Status
Subject Wisconsin State Trunk Highway system E726172 entity
Predicate hasComponent P35 FINISHED
Object Wisconsin State Trunk Highway 59
Wisconsin State Trunk Highway 59 is an east–west state highway in Wisconsin that connects several communities in the southern part of the state.
E1920518 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 State Trunk Highway 59 | Statement: [Wisconsin State Trunk Highway system, hasComponent, Wisconsin State Trunk Highway 59]
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 State Trunk Highway 59
Triple: [Wisconsin State Trunk Highway system, hasComponent, Wisconsin State Trunk Highway 59]
Generated description
Wisconsin State Trunk Highway 59 is an east–west state highway in Wisconsin that connects several communities in the southern part of the state.

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_69f03198be14819098fa74e48b3749bf completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f658219cbc8190a8eaa708df182f61 completed May 2, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2856cd98c48190b877fdfbd0ac464c completed June 9, 2026, 6:09 p.m.
NEDg Description generation batch_6a2857cafff48190b89251d97dd531f4 completed June 9, 2026, 6:13 p.m.
NED2 Entity disambiguation (via description) batch_6a28588218848190b284d41d25070731 completed June 9, 2026, 6:16 p.m.
Created at: April 28, 2026, 6:12 a.m.