Triple

T32515648
Position Surface form Disambiguated ID Type / Status
Subject Сенатская площадь E831053 entity
Predicate расположенаУ P105947 FINISHED
Object Исаакиевская площадь
Исаакиевская площадь — одна из центральных и исторически значимых площадей Санкт-Петербурга, расположенная у Исаакиевского собора и окружённая важными административными и архитектурными зданиями.
E2015956 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: Исаакиевская площадь | Statement: [Сенатская площадь, расположенаУ, Исаакиевская площадь]
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: Исаакиевская площадь
Triple: [Сенатская площадь, расположенаУ, Исаакиевская площадь]
Generated description
Исаакиевская площадь — одна из центральных и исторически значимых площадей Санкт-Петербурга, расположенная у Исаакиевского собора и окружённая важными административными и архитектурными зданиями.

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_69f3492318348190ba37fb6b5f1d67f4 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c4a1d7f48190b47a3d532522e735 completed May 3, 2026, 3:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34928b79a08190bf44c0ac0aec36a8 completed June 19, 2026, 12:51 a.m.
NEDg Description generation batch_6a34935caff8819097c46aa1de42eb95 completed June 19, 2026, 12:54 a.m.
NED2 Entity disambiguation (via description) batch_6a3493c4efb881909c333ffbe0642910 completed June 19, 2026, 12:56 a.m.
Created at: May 1, 2026, 1 a.m.