Triple

T36010021
Position Surface form Disambiguated ID Type / Status
Subject Department of Health (Tasmania) E1041378 entity
Predicate oversees P46 FINISHED
Object Launceston General Hospital
Launceston General Hospital is a major public teaching and referral hospital in Launceston, Tasmania, providing a wide range of acute and specialist healthcare services to the region.
E2165406 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: Launceston General Hospital | Statement: [Department of Health (Tasmania), oversees, Launceston General Hospital]
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: Launceston General Hospital
Triple: [Department of Health (Tasmania), oversees, Launceston General Hospital]
Generated description
Launceston General Hospital is a major public teaching and referral hospital in Launceston, Tasmania, providing a wide range of acute and specialist healthcare services to the region.

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_69f76e2a02208190aedd1f9025a8b300 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7acb2bca08190acb3c310ada7a8d1 completed May 3, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38bff7cf80819095eaafd6aa7cbc7a completed June 22, 2026, 4:54 a.m.
NEDg Description generation batch_6a38c0a93ce881908c7f774b519e5247 completed June 22, 2026, 4:57 a.m.
NED2 Entity disambiguation (via description) batch_6a38c146238481909a2d82cd040468f6 completed June 22, 2026, 4:59 a.m.
Created at: May 3, 2026, 4:07 p.m.