Triple

T37111810
Position Surface form Disambiguated ID Type / Status
Subject Minnesota state forest system E919009 entity
Predicate hasPart P35 FINISHED
Object Grand Portage State Forest
Grand Portage State Forest is a large public forest in northeastern Minnesota known for its rugged North Shore landscapes, extensive trails, and outdoor recreation opportunities.
E2225312 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: Grand Portage State Forest | Statement: [Minnesota state forest system, hasPart, Grand Portage 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: Grand Portage State Forest
Triple: [Minnesota state forest system, hasPart, Grand Portage State Forest]
Generated description
Grand Portage State Forest is a large public forest in northeastern Minnesota known for its rugged North Shore landscapes, extensive trails, and outdoor recreation opportunities.

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_69f76e9b99c8819096164b21ff5bd996 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb3011df288190a2721c138dd24d53 completed May 6, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4076e0149c8190bc6a398057d6d8bf completed June 28, 2026, 1:20 a.m.
NEDg Description generation batch_6a407793fcf881909f668943a27834ca completed June 28, 2026, 1:23 a.m.
NED2 Entity disambiguation (via description) batch_6a40781d2d808190b2118b042356795c completed June 28, 2026, 1:25 a.m.
Created at: May 3, 2026, 4:14 p.m.