Triple

T27296135
Position Surface form Disambiguated ID Type / Status
Subject Shrewsbury, Pennsylvania E688768 entity
Predicate roadAccess P385 FINISHED
Object Pennsylvania Route 851
Pennsylvania Route 851 is a state highway in southern Pennsylvania that runs east–west through rural York County, connecting small towns and providing access to the Maryland state line.
E2234621 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: Pennsylvania Route 851 | Statement: [Shrewsbury, Pennsylvania, roadAccess, Pennsylvania Route 851]
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: Pennsylvania Route 851
Triple: [Shrewsbury, Pennsylvania, roadAccess, Pennsylvania Route 851]
Generated description
Pennsylvania Route 851 is a state highway in southern Pennsylvania that runs east–west through rural York County, connecting small towns and providing access to the Maryland state line.

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_69ef355a96308190a2bed991525fb278 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6277ff9848190958c203e511b1393 completed May 2, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40a7d31d908190b1381f3c5680f798 completed June 28, 2026, 4:49 a.m.
NEDg Description generation batch_6a40a991095c8190a77e79a757e7ea95 completed June 28, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_6a40a9ffe2688190ad8c76e103b9eace completed June 28, 2026, 4:58 a.m.
Created at: April 27, 2026, 11:18 a.m.