Triple

T25226650
Position Surface form Disambiguated ID Type / Status
Subject John Nicholas Brown II E632103 entity
Predicate spouse P13 FINISHED
Object Anne Seddon Kinsolving Brown
Anne Seddon Kinsolving Brown was an American collector and philanthropist best known for assembling a major collection of military and naval history materials that became a cornerstone of Brown University's John Hay Library.
E1691380 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: Anne Seddon Kinsolving Brown | Statement: [John Nicholas Brown II, spouse, Anne Seddon Kinsolving Brown]
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: Anne Seddon Kinsolving Brown
Triple: [John Nicholas Brown II, spouse, Anne Seddon Kinsolving Brown]
Generated description
Anne Seddon Kinsolving Brown was an American collector and philanthropist best known for assembling a major collection of military and naval history materials that became a cornerstone of Brown University's John Hay Library.

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_69e75a8e0f688190a7aebe9a4815e25b completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f47cc42b808190977730a9ec2de79c completed May 1, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10c1155c5c8190afd438a84a6f6afb completed May 22, 2026, 8:48 p.m.
NEDg Description generation batch_6a10c403c7b88190ba63867cdcf0982e completed May 22, 2026, 9 p.m.
NED2 Entity disambiguation (via description) batch_6a10c47aae308190ae8e8d59424cc8e7 completed May 22, 2026, 9:02 p.m.
Created at: April 21, 2026, 1:03 p.m.