Triple

T25989458
Position Surface form Disambiguated ID Type / Status
Subject New Windsor, Maryland E646302 entity
Predicate hasNotableBuilding P1544 FINISHED
Object New Windsor Bank Building
The New Windsor Bank Building is a historic commercial structure in New Windsor, Maryland, notable for its role in the town’s early financial and civic life.
E1704269 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: New Windsor Bank Building | Statement: [New Windsor, Maryland, hasNotableBuilding, New Windsor Bank Building]
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: New Windsor Bank Building
Triple: [New Windsor, Maryland, hasNotableBuilding, New Windsor Bank Building]
Generated description
The New Windsor Bank Building is a historic commercial structure in New Windsor, Maryland, notable for its role in the town’s early financial and civic life.

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_69e77e881fc08190ba1c8dc7e2a07f97 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f605469f7881909fb9d981d79def18 completed May 2, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a110793e7ec8190970434cda08ebd49 completed May 23, 2026, 1:49 a.m.
NEDg Description generation batch_6a11080f37c08190b1e814533c85f8f2 completed May 23, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_6a1108aa194481908986a597992ffbac completed May 23, 2026, 1:53 a.m.
Created at: April 22, 2026, 8:55 a.m.