Triple

T28016135
Position Surface form Disambiguated ID Type / Status
Subject V-320 E707548 entity
Predicate usedAtPlant P122286 FINISHED
Object Temelín Nuclear Power Station
Temelín Nuclear Power Station is the largest nuclear power plant in the Czech Republic, featuring Soviet-designed VVER pressurized water reactors that supply a significant share of the country’s electricity.
E1799454 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: Temelín Nuclear Power Station | Statement: [V-320, usedAtPlant, Temelín Nuclear Power Station]
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: Temelín Nuclear Power Station
Triple: [V-320, usedAtPlant, Temelín Nuclear Power Station]
Generated description
Temelín Nuclear Power Station is the largest nuclear power plant in the Czech Republic, featuring Soviet-designed VVER pressurized water reactors that supply a significant share of the country’s electricity.

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_69ef96baf3a881909a2b63844185dddd completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63c0796288190a5936b67d90abd00 completed May 2, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b8a239d081908692b9e4fefcc574 completed May 26, 2026, 3:13 p.m.
NEDg Description generation batch_6a15bba2f1008190a0474d7cf231e2fd completed May 26, 2026, 3:26 p.m.
NED2 Entity disambiguation (via description) batch_6a15bca7a2808190856b1965f78418eb completed May 26, 2026, 3:30 p.m.
Created at: April 27, 2026, 8:07 p.m.