Triple

T24016341
Position Surface form Disambiguated ID Type / Status
Subject Jefferson, Maryland E594685 entity
Predicate hasHistoricDistrict P295 FINISHED
Object Jefferson Historic District
Jefferson Historic District is a preserved area in Jefferson, Maryland, known for its collection of historic buildings that reflect the town’s 18th- and 19th-century architectural and cultural heritage.
E1614332 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: Jefferson Historic District | Statement: [Jefferson, Maryland, hasHistoricDistrict, Jefferson Historic District]
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: Jefferson Historic District
Triple: [Jefferson, Maryland, hasHistoricDistrict, Jefferson Historic District]
Generated description
Jefferson Historic District is a preserved area in Jefferson, Maryland, known for its collection of historic buildings that reflect the town’s 18th- and 19th-century architectural and cultural heritage.

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_69e288bc8f608190ac4af29f0bd1c744 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d5a3f5a08190b7170270c4fcf080 completed April 29, 2026, 9:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7ea262748190ac041b5f99bb1d26 completed May 21, 2026, 9:52 p.m.
NEDg Description generation batch_6a0f7faebc708190b9efb824ce89d875 completed May 21, 2026, 9:57 p.m.
NED2 Entity disambiguation (via description) batch_6a0f8061997c819086460c6c57cd8c12 completed May 21, 2026, 10 p.m.
Created at: April 17, 2026, 9:42 p.m.