Triple

T27149886
Position Surface form Disambiguated ID Type / Status
Subject A121 Sortavala highway E682357 entity
Predicate passesThrough P225 FINISHED
Object Karelia region
Karelia region is a historical and geographical area in northern Europe, largely within northwestern Russia, known for its forests, lakes, and distinct Karelian culture.
E1773161 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: Karelia region | Statement: [A121 Sortavala highway, passesThrough, Karelia region]
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: Karelia region
Triple: [A121 Sortavala highway, passesThrough, Karelia region]
Generated description
Karelia region is a historical and geographical area in northern Europe, largely within northwestern Russia, known for its forests, lakes, and distinct Karelian culture.

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_69eefaceb2a08190b9659b7f730629f5 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f624c8b4148190990ea6bd13e9e271 completed May 2, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b220cef88190aa6ed453692e3064 completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b336f16881908177da118f0043a5 completed May 24, 2026, 8:13 a.m.
NED2 Entity disambiguation (via description) batch_6a12b39083908190b689245002e150c7 completed May 24, 2026, 8:15 a.m.
Created at: April 27, 2026, 9:13 a.m.