Triple

T23542051
Position Surface form Disambiguated ID Type / Status
Subject Downtown Holyoke Historic District E577778 entity
Predicate contains P35 FINISHED
Object Lyman Street
Lyman Street is a historic thoroughfare in downtown Holyoke, Massachusetts, known for its role in the city’s 19th- and early 20th-century commercial and industrial development.
E2192002 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: Lyman Street | Statement: [Downtown Holyoke Historic District, contains, Lyman Street]
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: Lyman Street
Triple: [Downtown Holyoke Historic District, contains, Lyman Street]
Generated description
Lyman Street is a historic thoroughfare in downtown Holyoke, Massachusetts, known for its role in the city’s 19th- and early 20th-century commercial and industrial development.

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_69e245f9d5d08190a4a20004e1784e20 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae1cb8b48190b51dd83b9fb116fe completed April 29, 2026, 7:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3a0938257081908a34f533c8601057 completed June 23, 2026, 4:19 a.m.
NEDg Description generation batch_6a3a0bbb76ec8190a93578ed3265ccf0 completed June 23, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_6a3a0c1709308190ab8d54e08845c2d5 completed June 23, 2026, 4:31 a.m.
Created at: April 17, 2026, 6:10 p.m.