Triple

T26540990
Position Surface form Disambiguated ID Type / Status
Subject Karl Rolvaag E671385 entity
Predicate officeAssumedFrom P54607 FINISHED
Object Elmer L. Andersen
Elmer L. Andersen was an American businessman and Republican politician who served as governor of Minnesota in the early 1960s and was known for his progressive policies and philanthropy.
 E1813652 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: Elmer L. Andersen | Statement: [Karl Rolvaag, officeAssumedFrom, Elmer L. Andersen]
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: Elmer L. Andersen
Triple: [Karl Rolvaag, officeAssumedFrom, Elmer L. Andersen]
Generated description
Elmer L. Andersen was an American businessman and Republican politician who served as governor of Minnesota in the early 1960s and was known for his progressive policies and philanthropy.

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_69eeb3206e748190b90c85cc81f38c91 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f61431eb008190affb2b34864b3e8a completed May 2, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a162780dc0c81908e1b9b7f0dfb8e8c completed May 26, 2026, 11:06 p.m.
NEDg Description generation batch_6a1628f366d88190b10dda8b0ab63762 completed May 26, 2026, 11:12 p.m.
NED2 Entity disambiguation (via description) batch_6a16297370d08190a0088aa14476bb1f completed May 26, 2026, 11:14 p.m.
Created at: April 27, 2026, 1:41 a.m.