Triple

T37392107
Position Surface form Disambiguated ID Type / Status
Subject Maryland Route 165 near Pylesville E928742 entity
Predicate locatedIn P40 FINISHED
Object Pylesville, Maryland
Pylesville, Maryland is a small unincorporated community in Harford County known for its rural character and location in the northern part of the state near the Pennsylvania border.
E2285197 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: Pylesville, Maryland | Statement: [Maryland Route 165 near Pylesville, locatedIn, Pylesville, Maryland]
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: Pylesville, Maryland
Triple: [Maryland Route 165 near Pylesville, locatedIn, Pylesville, Maryland]
Generated description
Pylesville, Maryland is a small unincorporated community in Harford County known for its rural character and location in the northern part of the state near the Pennsylvania border.

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_69f76ebb10c481909b54b9dba263e29f completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8d3a3af88190a3dd8307a751be2d completed May 6, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a45030830e0819086aea974d7b7e85d completed July 1, 2026, 12:07 p.m.
NEDg Description generation batch_6a4506e718588190835a4bd44a4f15d3 completed July 1, 2026, 12:24 p.m.
NED2 Entity disambiguation (via description) batch_6a453f3cc50881908a4274a365d7a1c9 completed July 1, 2026, 4:24 p.m.
Created at: May 3, 2026, 4:16 p.m.