Triple

T28232806
Position Surface form Disambiguated ID Type / Status
Subject Chessington South railway station E711798 entity
Predicate designedBy P184 FINISHED
Object James Robb Scott
James Robb Scott was a prominent 20th-century British architect best known for his work on railway architecture for the Southern Railway and later British Railways.
E1807699 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: James Robb Scott | Statement: [Chessington South railway station, designedBy, James Robb Scott]
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: James Robb Scott
Triple: [Chessington South railway station, designedBy, James Robb Scott]
Generated description
James Robb Scott was a prominent 20th-century British architect best known for his work on railway architecture for the Southern Railway and later British Railways.

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_69efb51ece308190b8c269a057e36652 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f6438995e48190a2d1b7caf425d0ab completed May 2, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15e6cdc1b88190b20714729188d9eb completed May 26, 2026, 6:30 p.m.
NEDg Description generation batch_6a15e740ebcc8190b862c2e82830c190 completed May 26, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_6a15ea29e18c8190960e302799684656 completed May 26, 2026, 6:44 p.m.
Created at: April 27, 2026, 10:52 p.m.