Triple

T32408419
Position Surface form Disambiguated ID Type / Status
Subject FirstEnergy E828144 entity
Predicate operatesIn P82 FINISHED
Object Virginia
Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American history, diverse geography from Atlantic coastline to Appalachian Mountains, and significant political and economic influence.
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: [FirstEnergy, operatesIn, 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: [FirstEnergy, operatesIn, Virginia]
Generated description
Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American history, diverse geography from Atlantic coastline to Appalachian Mountains, and significant political and economic influence.

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_69f34919f300819092b541c6277cd68a completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c25100448190a63e488c812f9e18 completed May 3, 2026, 3:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a344f1c20b88190b08670fbbecff652 completed June 18, 2026, 8:03 p.m.
NEDg Description generation batch_6a344fc15a7481908e2e9774dcc7f2df completed June 18, 2026, 8:06 p.m.
NED2 Entity disambiguation (via description) batch_6a3450b1ef4081909cdb8148e80f7dde completed June 18, 2026, 8:10 p.m.
Created at: May 1, 2026, 12:53 a.m.