Triple

T31587447
Position Surface form Disambiguated ID Type / Status
Subject MediFund E805991 entity
Predicate decisionMaker P6016 FINISHED
Object MediFund Committees at approved institutions
MediFund Committees at approved institutions are designated bodies that assess and approve financial assistance applications under Singapore’s MediFund scheme for patients who cannot afford their medical bills.
 E1969630 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: MediFund Committees at approved institutions | Statement: [MediFund, decisionMaker, MediFund Committees at approved institutions]
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: MediFund Committees at approved institutions
Triple: [MediFund, decisionMaker, MediFund Committees at approved institutions]
Generated description
MediFund Committees at approved institutions are designated bodies that assess and approve financial assistance applications under Singapore’s MediFund scheme for patients who cannot afford their medical bills.

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_69f348d4891c8190b02bae3c8ecb68b7 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a80df52c819092af926fd63fa1a3 completed May 3, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b564e373c81908084c5e5514c2f3b completed June 12, 2026, 12:43 a.m.
NEDg Description generation batch_6a2b570e0ee88190898d1159d69ef4ce completed June 12, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_6a2b6cb9655c8190955a25f2c262c5e5 completed June 12, 2026, 2:19 a.m.
Created at: April 30, 2026, 10:26 p.m.