Triple

T21656002
Position Surface form Disambiguated ID Type / Status
Subject Reisterstown Road E534466 entity
Predicate hasJunctionWith P1018 FINISHED
Object Northern Parkway
Northern Parkway is a major east–west arterial road in Baltimore, Maryland, connecting several neighborhoods and intersecting key routes across the city.
 E1640778 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: Northern Parkway | Statement: [Reisterstown Road, hasJunctionWith, Northern Parkway]
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: Northern Parkway
Triple: [Reisterstown Road, hasJunctionWith, Northern Parkway]
Generated description
Northern Parkway is a major east–west arterial road in Baltimore, Maryland, connecting several neighborhoods and intersecting key routes across the city.

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_69e0c467e1f48190af2650b19175abc4 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef59185b208190a2cf4b8f54a2c231 completed April 27, 2026, 12:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0ff820e0908190a5ced13f1ffb7eda completed May 22, 2026, 6:30 a.m.
NEDg Description generation batch_6a0ff93a0dec81909163580a48548e9a completed May 22, 2026, 6:35 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff9d952ec81908a5b2640c263e21d completed May 22, 2026, 6:38 a.m.
Created at: April 16, 2026, 6:36 p.m.