Triple

T24973871
Position Surface form Disambiguated ID Type / Status
Subject Transportation in Montgomery County, Maryland E624963 entity
Predicate majorCorridor P3034 FINISHED
Object Veirs Mill Road
Veirs Mill Road is a key arterial roadway in Montgomery County, Maryland, connecting several suburban communities and serving as an important commuter and transit route.
E2288884 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: Veirs Mill Road | Statement: [Transportation in Montgomery County, Maryland, majorCorridor, Veirs Mill Road]
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: Veirs Mill Road
Triple: [Transportation in Montgomery County, Maryland, majorCorridor, Veirs Mill Road]
Generated description
Veirs Mill Road is a key arterial roadway in Montgomery County, Maryland, connecting several suburban communities and serving as an important commuter and transit route.

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_69e2ff24512481908e9a72315b8d0354 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f444df53b481909c407f9124708b0b completed May 1, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5ae89653f48190a4d4d7ed5dd9bb80 completed July 18, 2026, 2:44 a.m.
NEDg Description generation batch_6a5ae917ac6081908c155e04066220f8 completed July 18, 2026, 2:46 a.m.
NED2 Entity disambiguation (via description) batch_6a5ae966aa7c8190a53aae09e450118e completed July 18, 2026, 2:48 a.m.
Created at: April 18, 2026, 6:01 a.m.