Triple

T28982335
Position Surface form Disambiguated ID Type / Status
Subject Noah’s Ark Children’s Hospital for Wales E734584 entity
Predicate supportedBy P67 FINISHED
Object Noah’s Ark Charity
Noah’s Ark Charity is a fundraising organization dedicated to supporting the Noah’s Ark Children’s Hospital for Wales and enhancing healthcare services for children across Wales.
 E1844608 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: Noah’s Ark Charity | Statement: [Noah’s Ark Children’s Hospital for Wales, supportedBy, Noah’s Ark Charity]
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: Noah’s Ark Charity
Triple: [Noah’s Ark Children’s Hospital for Wales, supportedBy, Noah’s Ark Charity]
Generated description
Noah’s Ark Charity is a fundraising organization dedicated to supporting the Noah’s Ark Children’s Hospital for Wales and enhancing healthcare services for children across Wales.

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_69f05b0dd9b481908b7901e1c95ff6b2 completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65ee54f6c819095b37e6a00595694 completed May 2, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2505af8fd081908b16603307b801ed completed June 7, 2026, 5:46 a.m.
NEDg Description generation batch_6a2509d511b481908fb354a22e7ee542 completed June 7, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a250e2aedec8190b56183a021e81469 completed June 7, 2026, 6:22 a.m.
Created at: April 28, 2026, 9:12 a.m.