Triple

T36668366
Position Surface form Disambiguated ID Type / Status
Subject William Stroudley E905333 entity
Predicate designed P184 FINISHED
Object LB&SCR G class locomotives
The LB&SCR G class locomotives were a series of late 19th-century British steam tank engines built for the London, Brighton and South Coast Railway, primarily used for suburban and branch line passenger services.
E2199854 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: LB&SCR G class locomotives | Statement: [William Stroudley, designed, LB&SCR G class locomotives]
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: LB&SCR G class locomotives
Triple: [William Stroudley, designed, LB&SCR G class locomotives]
Generated description
The LB&SCR G class locomotives were a series of late 19th-century British steam tank engines built for the London, Brighton and South Coast Railway, primarily used for suburban and branch line passenger services.

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_69f76e6f10008190aea41746aa1b186e completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c79c2fb0819097c2a5113f55e8fb completed May 3, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3d178870888190b0015bf445f30dc8 completed June 25, 2026, 11:56 a.m.
NEDg Description generation batch_6a3d1828cb4081908806cc837aac45a8 completed June 25, 2026, 11:59 a.m.
NED2 Entity disambiguation (via description) batch_6a3dcecff9488190829ea20f5bdde66c completed June 26, 2026, 12:58 a.m.
Created at: May 3, 2026, 4:12 p.m.