Triple

T34703908
Position Surface form Disambiguated ID Type / Status
Subject Milwaukee CSA E1000447 entity
Predicate includesMicropolitanArea P35912 FINISHED
Object Beaver Dam micropolitan area
The Beaver Dam micropolitan area is a small urban region in Wisconsin centered around the city of Beaver Dam, functioning as part of the broader Milwaukee combined statistical area.
E2107772 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: Beaver Dam micropolitan area | Statement: [Milwaukee CSA, includesMicropolitanArea, Beaver Dam micropolitan area]
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: Beaver Dam micropolitan area
Triple: [Milwaukee CSA, includesMicropolitanArea, Beaver Dam micropolitan area]
Generated description
The Beaver Dam micropolitan area is a small urban region in Wisconsin centered around the city of Beaver Dam, functioning as part of the broader Milwaukee combined statistical area.

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_69f76dab937881909c86f1b9ad50445f completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77972d82481909d734ac5433554b4 completed May 3, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a375308293c8190bcd103929d846adf completed June 21, 2026, 2:57 a.m.
NEDg Description generation batch_6a3753bc9a80819080ac22952c59dd26 completed June 21, 2026, 3 a.m.
NED2 Entity disambiguation (via description) batch_6a375497c5288190aed9f037fbe3c969 completed June 21, 2026, 3:03 a.m.
Created at: May 3, 2026, 3:59 p.m.