Triple

T27887364
Position Surface form Disambiguated ID Type / Status
Subject Lhasa Municipal Government E705266 entity
Predicate hasBranch P35 FINISHED
Object Lhasa Municipal Health Commission
The Lhasa Municipal Health Commission is the local government body responsible for overseeing public health policy, medical services, and disease prevention within the city of Lhasa.
E1805172 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: Lhasa Municipal Health Commission | Statement: [Lhasa Municipal Government, hasBranch, Lhasa Municipal Health Commission]
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: Lhasa Municipal Health Commission
Triple: [Lhasa Municipal Government, hasBranch, Lhasa Municipal Health Commission]
Generated description
The Lhasa Municipal Health Commission is the local government body responsible for overseeing public health policy, medical services, and disease prevention within the city of Lhasa.

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_69ef96b39c448190a9b3aa6672a5168f completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f639b25b2c819090f30ea43ffae5ad completed May 2, 2026, 5:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15d78016e08190b98d45de1a81ec99 completed May 26, 2026, 5:25 p.m.
NEDg Description generation batch_6a15da345bf481908136f95c41489006 completed May 26, 2026, 5:36 p.m.
NED2 Entity disambiguation (via description) batch_6a15daaf33588190b5aa74d272349389 completed May 26, 2026, 5:38 p.m.
Created at: April 27, 2026, 6:34 p.m.