Triple

T26192937
Position Surface form Disambiguated ID Type / Status
Subject papers and correspondence of George Washington E655015 entity
Predicate associatedWithPlace P2830 FINISHED
Object Virginia
Virginia is a historically significant U.S. state, central to early American colonial history and the life and leadership of George Washington.
E5410 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: Virginia | Statement: [papers and correspondence of George Washington, associatedWithPlace, Virginia]
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: Virginia
Triple: [papers and correspondence of George Washington, associatedWithPlace, Virginia]
Generated description
Virginia is a historically significant U.S. state, central to early American colonial history and the life and leadership of George Washington.

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_69ee5b48236c81908fe385b6afc4f60b completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60ca4397481908a10249146f7c5ef completed May 2, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118f949240819080874141ea0f12d8 completed May 23, 2026, 11:29 a.m.
NEDg Description generation batch_6a119109636881908e86483c00df11ce completed May 23, 2026, 11:35 a.m.
NED2 Entity disambiguation (via description) batch_6a11918f1dd48190be4ff6b151a01943 completed May 23, 2026, 11:37 a.m.
Created at: April 26, 2026, 8:45 p.m.