Triple

T27684955
Position Surface form Disambiguated ID Type / Status
Subject people's courts of the People's Republic of China E698001 entity
Predicate includes P1393 FINISHED
Object internet courts
Internet courts are specialized Chinese judicial bodies that conduct most proceedings online to handle internet-related civil and administrative disputes such as e-commerce, online copyright, and digital contract cases.
E1782287 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: internet courts | Statement: [people's courts of the People's Republic of China, includes, internet courts]
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: internet courts
Triple: [people's courts of the People's Republic of China, includes, internet courts]
Generated description
Internet courts are specialized Chinese judicial bodies that conduct most proceedings online to handle internet-related civil and administrative disputes such as e-commerce, online copyright, and digital contract cases.

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_69ef590df8708190af5488f0638e790c completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f63572ae688190b6529409b47e1ce8 completed May 2, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12daafa5dc81908fa445ad0a234e77 completed May 24, 2026, 11:02 a.m.
NEDg Description generation batch_6a12db425798819097c2f19d2aa6baaa completed May 24, 2026, 11:04 a.m.
NED2 Entity disambiguation (via description) batch_6a12dbac16bc8190aa2c654274fbcb3b completed May 24, 2026, 11:06 a.m.
Created at: April 27, 2026, 2:49 p.m.