Triple

T27274935
Position Surface form Disambiguated ID Type / Status
Subject Sherburne County, Minnesota E688160 entity
Predicate hasProtectedArea P855 FINISHED
Object Sand Dunes State Forest
Sand Dunes State Forest is a Minnesota state forest known for its unique sandy soils, rolling dunes, and pine woodlands that provide recreation and wildlife habitat.
E1870299 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: Sand Dunes State Forest | Statement: [Sherburne County, Minnesota, hasProtectedArea, Sand Dunes State Forest]
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: Sand Dunes State Forest
Triple: [Sherburne County, Minnesota, hasProtectedArea, Sand Dunes State Forest]
Generated description
Sand Dunes State Forest is a Minnesota state forest known for its unique sandy soils, rolling dunes, and pine woodlands that provide recreation and wildlife habitat.

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_69ef3558cf8881909595ef89daf6e14a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6272737c08190b3d33f2c92fdf2ff completed May 2, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f0e307e88190a11761a5f81a627d completed June 7, 2026, 10:29 p.m.
NEDg Description generation batch_6a25f67f6bc88190af7c53158288e611 completed June 7, 2026, 10:53 p.m.
NED2 Entity disambiguation (via description) batch_6a25fab29d588190a93a4b1043036423 completed June 7, 2026, 11:11 p.m.
Created at: April 27, 2026, 11:02 a.m.