Triple

T26147653
Position Surface form Disambiguated ID Type / Status
Subject Kerr Dam E659722 entity
Predicate locatedOnBorderOf P224 FINISHED
Object Virginia
Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American colonial history, the Revolutionary and Civil Wars, and as the home state of numerous U.S. presidents.
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: [Kerr Dam, locatedOnBorderOf, 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: [Kerr Dam, locatedOnBorderOf, Virginia]
Generated description
Virginia is a U.S. state in the Mid-Atlantic and Southeastern regions, known for its pivotal role in American colonial history, the Revolutionary and Civil Wars, and as the home state of numerous U.S. presidents.

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_69ee5bc496a88190af7deb7ab5e081de completed April 26, 2026, 6:39 p.m.
NER Named-entity recognition batch_69f60be993dc819083bd352e2b444611 completed May 2, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1127560b9c8190b06a667dfb0d9926 completed May 23, 2026, 4:04 a.m.
NEDg Description generation batch_6a11539cf7c48190b2014ba36bd66cf3 completed May 23, 2026, 7:13 a.m.
NED2 Entity disambiguation (via description) batch_6a1154903eac8190901702bf0c3e452a completed May 23, 2026, 7:17 a.m.
Created at: April 26, 2026, 8:23 p.m.