Triple

T37069839
Position Surface form Disambiguated ID Type / Status
Subject Blackberry Township, Kane County, Illinois E917544 entity
Predicate subdivisionName P747 FINISHED
Object Blackberry Township
Blackberry Township is a civil township located in Kane County, Illinois, known for its mix of rural landscapes and growing suburban communities.
E2212043 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: Blackberry Township | Statement: [Blackberry Township, Kane County, Illinois, subdivisionName, Blackberry 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: Blackberry Township
Triple: [Blackberry Township, Kane County, Illinois, subdivisionName, Blackberry Township]
Generated description
Blackberry Township is a civil township located in Kane County, Illinois, known for its mix of rural landscapes and growing suburban communities.

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_69f76e9771e08190a690834e3cd20654 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb2f9389448190bfc189b711d9e1ea completed May 6, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3efdbc6e808190b33edb32fb512786 completed June 26, 2026, 10:31 p.m.
NEDg Description generation batch_6a3efeafb124819087f472bb53b3c4e1 completed June 26, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_6a3eff31b0148190a5f314ce6a009c55 completed June 26, 2026, 10:37 p.m.
Created at: May 3, 2026, 4:14 p.m.