Triple

T22086068
Position Surface form Disambiguated ID Type / Status
Subject Hawley E545778 entity
Predicate hasNotableBearer P458 FINISHED
Object John B. Hawley
John B. Hawley was an American politician who served as a U.S. Representative from Illinois in the late 19th century.
E2290410 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: John B. Hawley | Statement: [Hawley, hasNotableBearer, John B. Hawley]
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: John B. Hawley
Triple: [Hawley, hasNotableBearer, John B. Hawley]
Generated description
John B. Hawley was an American politician who served as a U.S. Representative from Illinois in the late 19th century.

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_69e11e3523488190badd54b5d580c00d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f128ba24ac819082fc4aa274553481 completed April 28, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5bc7776738819087a88b347eb46e2e completed July 18, 2026, 6:35 p.m.
NEDg Description generation batch_6a5bc7e80d54819084d5f865d9fb781b completed July 18, 2026, 6:37 p.m.
NED2 Entity disambiguation (via description) batch_6a5bc8397c208190a804ba5f7f57635f completed July 18, 2026, 6:38 p.m.
Created at: April 16, 2026, 8:29 p.m.