Triple

T33007173
Position Surface form Disambiguated ID Type / Status
Subject RIIO price control E844533 entity
Predicate predecessor P97 FINISHED
Object RPI-X price control
RPI-X price control is a UK regulatory framework that capped utility companies’ prices by linking them to inflation (RPI) minus an efficiency factor (X) to incentivize cost reductions and protect consumers.
E2031583 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: RPI-X price control | Statement: [RIIO price control, predecessor, RPI-X price control]
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: RPI-X price control
Triple: [RIIO price control, predecessor, RPI-X price control]
Generated description
RPI-X price control is a UK regulatory framework that capped utility companies’ prices by linking them to inflation (RPI) minus an efficiency factor (X) to incentivize cost reductions and protect consumers.

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_69f3494e59f08190b9127c693e5c7e8f completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d27b24b88190adcbd9634b1b7885 completed May 3, 2026, 4:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34dacec4b081909ff2bd7951a9c541 completed June 19, 2026, 5:59 a.m.
NEDg Description generation batch_6a34db4fc32c8190a2277b24a9031669 completed June 19, 2026, 6:01 a.m.
NED2 Entity disambiguation (via description) batch_6a34dbec0c9c8190ac5b263151322aba completed June 19, 2026, 6:04 a.m.
Created at: May 1, 2026, 1:23 a.m.