Triple

T30195758
Position Surface form Disambiguated ID Type / Status
Subject Strelka (confluence of Oka and Volga rivers) E767624 entity
Predicate knownAs P39 FINISHED
Object Strelka
Strelka is a historic riverfront area in Nizhny Novgorod, Russia, located at the confluence of the Oka and Volga rivers and known for its panoramic views and cultural significance.
E1903885 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: Strelka | Statement: [Strelka (confluence of Oka and Volga rivers), knownAs, Strelka]
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: Strelka
Triple: [Strelka (confluence of Oka and Volga rivers), knownAs, Strelka]
Generated description
Strelka is a historic riverfront area in Nizhny Novgorod, Russia, located at the confluence of the Oka and Volga rivers and known for its panoramic views and cultural significance.

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_69f2247db1108190835c0727c97637c3 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67f86de74819091cb45049fb9e1f8 completed May 2, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27589a3e5c8190b7f147d244054ea6 completed June 9, 2026, 12:04 a.m.
NEDg Description generation batch_6a275a7e7e78819088b7aef8057de369 completed June 9, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_6a275b647ee08190a1590afaccf078b8 completed June 9, 2026, 12:16 a.m.
Created at: April 29, 2026, 7:29 p.m.