Triple

T31558250
Position Surface form Disambiguated ID Type / Status
Subject Ilyich Square E805185 entity
Predicate hasNearbyMetroStation P26735 FINISHED
Object Ploshchad Ilyicha metro station
Ploshchad Ilyicha metro station is a Moscow Metro station on the Kalininskaya Line, serving the Ilyich Square area in central Moscow.
E2050481 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: Ploshchad Ilyicha metro station | Statement: [Ilyich Square, hasNearbyMetroStation, Ploshchad Ilyicha metro 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: Ploshchad Ilyicha metro station
Triple: [Ilyich Square, hasNearbyMetroStation, Ploshchad Ilyicha metro station]
Generated description
Ploshchad Ilyicha metro station is a Moscow Metro station on the Kalininskaya Line, serving the Ilyich Square area in central Moscow.

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_69f348d22e088190ad555d5bd42f9da0 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a7c67f188190bfe99ca25faf7c8d completed May 3, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35812eb9048190851cbe7e71ad5623 completed June 19, 2026, 5:49 p.m.
NEDg Description generation batch_6a3581ddeab88190b15f2f974ef67e0e completed June 19, 2026, 5:52 p.m.
NED2 Entity disambiguation (via description) batch_6a3582372b908190be6d6197e7e4ea92 completed June 19, 2026, 5:53 p.m.
Created at: April 30, 2026, 10:14 p.m.