Triple

T34681244
Position Surface form Disambiguated ID Type / Status
Subject Chinese nuclear industry E890627 entity
Predicate domesticDesign P19107 FINISHED
Object Linglong One small modular reactor
Linglong One is a Chinese-designed small modular nuclear reactor intended to provide flexible, safer, and more easily deployable low-carbon power generation.
E2107922 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: Linglong One small modular reactor | Statement: [Chinese nuclear industry, domesticDesign, Linglong One small modular reactor]
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: Linglong One small modular reactor
Triple: [Chinese nuclear industry, domesticDesign, Linglong One small modular reactor]
Generated description
Linglong One is a Chinese-designed small modular nuclear reactor intended to provide flexible, safer, and more easily deployable low-carbon power generation.

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_69f349dabc008190a18999c26682ed47 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7283fc3788190a409e1ad96655ad7 completed May 3, 2026, 10:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3752f32914819088d7f176ea75a258 completed June 21, 2026, 2:56 a.m.
NEDg Description generation batch_6a37538a0d948190949592c8f833958c completed June 21, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_6a37541fa8d48190aef474f094893f32 completed June 21, 2026, 3:01 a.m.
Created at: May 1, 2026, 2:05 a.m.