Triple

T34806446
Position Surface form Disambiguated ID Type / Status
Subject Riddle’s Court E1003369 entity
Predicate operator P179 FINISHED
Object Scottish Historic Buildings Trust
The Scottish Historic Buildings Trust is a conservation charity dedicated to rescuing, restoring, and finding sustainable new uses for significant historic buildings across Scotland.
E2112713 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: Scottish Historic Buildings Trust | Statement: [Riddle’s Court, operator, Scottish Historic Buildings Trust]
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: Scottish Historic Buildings Trust
Triple: [Riddle’s Court, operator, Scottish Historic Buildings Trust]
Generated description
The Scottish Historic Buildings Trust is a conservation charity dedicated to rescuing, restoring, and finding sustainable new uses for significant historic buildings across Scotland.

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_69f76db600b88190989abdf08fce3b27 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a8e286481909852ed240c92b4aa completed May 3, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a376faf72bc8190a16bb82d4c132d02 completed June 21, 2026, 4:59 a.m.
NEDg Description generation batch_6a37703823ac81908261228f65fcfa4b completed June 21, 2026, 5:01 a.m.
NED2 Entity disambiguation (via description) batch_6a377178c0b88190b9182e381ed323da completed June 21, 2026, 5:07 a.m.
Created at: May 3, 2026, 3:59 p.m.