Triple

T30092453
Position Surface form Disambiguated ID Type / Status
Subject UK Data Archive E764770 entity
Predicate collaboratesWith P37 FINISHED
Object UK Data Service
The UK Data Service is a national digital infrastructure that provides access to a wide range of social, economic, and population data for research, teaching, and policy-making in the UK.
E764770 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: UK Data Service | Statement: [UK Data Archive, collaboratesWith, UK Data Service]
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: UK Data Service
Triple: [UK Data Archive, collaboratesWith, UK Data Service]
Generated description
The UK Data Service is a national digital infrastructure that provides access to a wide range of social, economic, and population data for research, teaching, and policy-making in 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_69f22473c0fc8190a926a8051b3b378b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67d8dc1988190835bb2ef7bf4f8b7 completed May 2, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274328b9e081908719e29052bf2685 completed June 8, 2026, 10:33 p.m.
NEDg Description generation batch_6a2743e9c3e88190acfe78f0d125df9d completed June 8, 2026, 10:36 p.m.
NED2 Entity disambiguation (via description) batch_6a27448fcf748190a4e15ef2f89f56f5 completed June 8, 2026, 10:39 p.m.
Created at: April 29, 2026, 7:06 p.m.