Triple

T24845000
Position Surface form Disambiguated ID Type / Status
Subject Brownell E621721 entity
Predicate bearer P11385 FINISHED
Object Herbert Brownell Jr.
Herbert Brownell Jr. was an American lawyer and politician best known for serving as U.S. Attorney General under President Dwight D. Eisenhower and for his significant role in advancing civil rights enforcement in the 1950s.
E1673745 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: Herbert Brownell Jr. | Statement: [Brownell, bearer, Herbert Brownell Jr.]
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: Herbert Brownell Jr.
Triple: [Brownell, bearer, Herbert Brownell Jr.]
Generated description
Herbert Brownell Jr. was an American lawyer and politician best known for serving as U.S. Attorney General under President Dwight D. Eisenhower and for his significant role in advancing civil rights enforcement in the 1950s.

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_69e2fac297e481909d3aedc75f585e42 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422cc83ec81909c9e64f09ff87590 completed May 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067a4063c8190a0bd362cb19aee84 completed May 22, 2026, 2:26 p.m.
NEDg Description generation batch_6a106883259c8190a5cd5759a46c4c40 completed May 22, 2026, 2:30 p.m.
NED2 Entity disambiguation (via description) batch_6a106b36ea6481908bd4a4ead6b40818 completed May 22, 2026, 2:41 p.m.
Created at: April 18, 2026, 5:19 a.m.