Triple

T25919592
Position Surface form Disambiguated ID Type / Status
Subject Devon County Council E653130 entity
Predicate oversees P46 FINISHED
Object Devon and Cornwall Pension Fund
The Devon and Cornwall Pension Fund is a local government pension scheme that manages retirement benefits for public sector employees in the Devon and Cornwall area of the UK.
E1700474 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: Devon and Cornwall Pension Fund | Statement: [Devon County Council, oversees, Devon and Cornwall Pension Fund]
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: Devon and Cornwall Pension Fund
Triple: [Devon County Council, oversees, Devon and Cornwall Pension Fund]
Generated description
The Devon and Cornwall Pension Fund is a local government pension scheme that manages retirement benefits for public sector employees in the Devon and Cornwall area of the UK.

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_69e7ab3e025c819086771607157f0015 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f603e894f8819087e42e19a711151a completed May 2, 2026, 2:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecd14bdc8190877ff1e4aa1a3a89 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ee0d6140819085164d18f1b0491c completed May 23, 2026, midnight
NED2 Entity disambiguation (via description) batch_6a10eef4d8048190aef9594650c273f8 completed May 23, 2026, 12:04 a.m.
Created at: April 22, 2026, 8:32 a.m.