Triple

T38126375
Position Surface form Disambiguated ID Type / Status
Subject Houghton Lake E952084 entity
Predicate locatedIn P40 FINISHED
Object Roscommon Township
Roscommon Township is a civil township in Roscommon County, Michigan, known for encompassing much of the shoreline and community around Houghton Lake, one of the state’s largest inland lakes.
E2258731 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: Roscommon Township | Statement: [Houghton Lake, locatedIn, Roscommon Township]
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: Roscommon Township
Triple: [Houghton Lake, locatedIn, Roscommon Township]
Generated description
Roscommon Township is a civil township in Roscommon County, Michigan, known for encompassing much of the shoreline and community around Houghton Lake, one of the state’s largest inland lakes.

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_69f76f083548819082bd2bbf53c79e8e completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc45e5d8f48190903dc020962a1785 completed May 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a417b23619c8190aab6c024dffaf336 completed June 28, 2026, 7:50 p.m.
NEDg Description generation batch_6a417b94e034819088aa6487a5a4ab5d completed June 28, 2026, 7:52 p.m.
NED2 Entity disambiguation (via description) batch_6a417bf2e0788190a6c9b4bc4224dc14 completed June 28, 2026, 7:54 p.m.
Created at: May 3, 2026, 4:21 p.m.