Triple

T33952856
Position Surface form Disambiguated ID Type / Status
Subject Star and Garter building E870484 entity
Predicate partOf P40 FINISHED
Object Richmond Hill conservation area
Richmond Hill conservation area is a protected historic and scenic district in Richmond, London, known for its notable architecture, green spaces, and views over the River Thames.
 E249121 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: Richmond Hill conservation area | Statement: [Star and Garter building, partOf, Richmond Hill conservation area]
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: Richmond Hill conservation area
Triple: [Star and Garter building, partOf, Richmond Hill conservation area]
Generated description
Richmond Hill conservation area is a protected historic and scenic district in Richmond, London, known for its notable architecture, green spaces, and views over the River Thames.

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_69f3499c2d7481909c953a5010227725 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7027b2d44819080965e33ad40e16a completed May 3, 2026, 8:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3689dfc1e8819092a9039c82c4692b completed June 20, 2026, 12:38 p.m.
NEDg Description generation batch_6a368a9e3d188190890e19e635d9cf9c completed June 20, 2026, 12:42 p.m.
NED2 Entity disambiguation (via description) batch_6a368b58c7848190b708ded1bbc44b60 completed June 20, 2026, 12:45 p.m.
Created at: May 1, 2026, 1:49 a.m.