Triple

T25515604
Position Surface form Disambiguated ID Type / Status
Subject Rockwell City, Iowa E639497 entity
Predicate nickname P55 FINISHED
Object Golden Buckle on the Corn Belt
"Golden Buckle on the Corn Belt" is a promotional nickname highlighting Rockwell City, Iowa’s prominent role in the fertile, corn-producing region of the American Midwest.
E1683704 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: Golden Buckle on the Corn Belt | Statement: [Rockwell City, Iowa, nickname, Golden Buckle on the Corn Belt]
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: Golden Buckle on the Corn Belt
Triple: [Rockwell City, Iowa, nickname, Golden Buckle on the Corn Belt]
Generated description
"Golden Buckle on the Corn Belt" is a promotional nickname highlighting Rockwell City, Iowa’s prominent role in the fertile, corn-producing region of the American Midwest.

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_69e75dbe32e48190a62d749a0ff2a96a completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f832d48c8190984c9370816aaf94 completed May 2, 2026, 1:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad82159881909b6b37d46c5350a3 completed May 22, 2026, 7:24 p.m.
NEDg Description generation batch_6a10adf21b3c8190a7388b1a74faf65e completed May 22, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a10af5c912c81908164148277047f40 completed May 22, 2026, 7:32 p.m.
Created at: April 21, 2026, 2:55 p.m.