Triple

T30183100
Position Surface form Disambiguated ID Type / Status
Subject Metrobus routes E767258 entity
Predicate servesArea 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 landscapes from Atlantic coastline to Appalachian Mountains, and major metropolitan areas near Washington, D.C.
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: [Metrobus routes, servesArea, 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: [Metrobus routes, servesArea, 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 landscapes from Atlantic coastline to Appalachian Mountains, and major metropolitan areas near Washington, D.C.

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_69f2247cc3d88190811dec3face94bf5 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67f43c8388190a0fce4ef4e392274 completed May 2, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276ee3af648190ae8a0e39052fd996 completed June 9, 2026, 1:39 a.m.
NEDg Description generation batch_6a276febe8e48190a61b0e20ac44ab06 completed June 9, 2026, 1:44 a.m.
NED2 Entity disambiguation (via description) batch_6a27708bfc588190abd7fa5039f5153a completed June 9, 2026, 1:46 a.m.
Created at: April 29, 2026, 7:26 p.m.