Triple

T35312110
Position Surface form Disambiguated ID Type / Status
Subject Krasnoyarsk Aluminum Plant E1019799 entity
Predicate knownAs P39 FINISHED
Object KrAZ
KrAZ is a major aluminum production facility located in Krasnoyarsk, Russia, and one of the largest such plants in the country.
E2134181 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: KrAZ | Statement: [Krasnoyarsk Aluminum Plant, knownAs, KrAZ]
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: KrAZ
Triple: [Krasnoyarsk Aluminum Plant, knownAs, KrAZ]
Generated description
KrAZ is a major aluminum production facility located in Krasnoyarsk, Russia, and one of the largest such plants in the country.

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_69f76de8b4c48190ae504b86185c474c completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7905842808190a4fc9917f0f4b60d completed May 3, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3819f1a4308190aad84cddf9bcd1ad completed June 21, 2026, 5:05 p.m.
NEDg Description generation batch_6a381aa74d8081908c07604175258249 completed June 21, 2026, 5:08 p.m.
NED2 Entity disambiguation (via description) batch_6a381b07217c819089d8c91dbe8a1e1e completed June 21, 2026, 5:10 p.m.
Created at: May 3, 2026, 4:03 p.m.