Triple

T23660017
Position Surface form Disambiguated ID Type / Status
Subject Maryland Route 103 E584417 entity
Predicate follows P134 FINISHED
Object Meadowridge Road
Meadowridge Road is a local thoroughfare in Maryland that serves as part of the route for Maryland Route 103.
E2285804 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: Meadowridge Road | Statement: [Maryland Route 103, follows, Meadowridge 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: Meadowridge Road
Triple: [Maryland Route 103, follows, Meadowridge Road]
Generated description
Meadowridge Road is a local thoroughfare in Maryland that serves as part of the route for Maryland Route 103.

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_69e248ffc0888190ae23c4731eb8b7ac completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b35f03448190834991c2a65ef0e4 completed April 29, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a4620db976c8190aa71f5e093473462 completed July 2, 2026, 8:27 a.m.
NEDg Description generation batch_6a46252badc0819081766bea89345bef completed July 2, 2026, 8:45 a.m.
NED2 Entity disambiguation (via description) batch_6a46270f0214819086cefa3c123a5cf1 completed July 2, 2026, 8:53 a.m.
Created at: April 17, 2026, 6:50 p.m.