Triple

T37941940
Position Surface form Disambiguated ID Type / Status
Subject Тимирязевская E946510 entity
Predicate название по происхождению P3325 FINISHED
Object улица Тимирязевская
Улица Тимирязевская — это московская улица, названная в честь русского естествоиспытателя Климента Тимирязева и проходящая через северную часть города.
 E2271314 NE FINISHED

How this triple was built (3 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: улица Тимирязевская | Statement: [Тимирязевская, название по происхождению, улица Тимирязевская]
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: улица Тимирязевская
Triple: [Тимирязевская, название по происхождению, улица Тимирязевская]
Generated description
Улица Тимирязевская — это московская улица, названная в честь русского естествоиспытателя Климента Тимирязева и проходящая через северную часть города.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: название по происхождению
Context triple: [Тимирязевская, название по происхождению, улица Тимирязевская]
  • A. nameOriginExplanation
    Indicates that an explanation is provided for the origin or derivation of a given name.
  • B. hasNameOrigin chosen
    Indicates that the origin or source of an entity’s name is specified by the related entity.
  • C. странаПроисхождения
    Indicates that one entity is the country from which another entity originates or comes.
  • D. natureOfName
    Indicates that the relationship specifies the type, origin, or semantic category of a given name.
  • E. nameEtymologyFor
    Indicates that one entity expresses or explains the origin or derivation of the name of another entity.
  • F. None of above.

Provenance (6 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_69f76ef531ac8190ae6d99e5786e76ec completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc7b78f9481909f4f8fc2e3fdcde1 completed May 6, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41cc8d5cd88190af33a4e61b4d8e9f completed June 29, 2026, 1:38 a.m.
NEDg Description generation batch_6a41ce0a6ae081909a96d33869cfde6b completed June 29, 2026, 1:44 a.m.
NED2 Entity disambiguation (via description) batch_6a41ceaec9a48190bd08361fd7b3362b completed June 29, 2026, 1:47 a.m.
PD Predicate disambiguation batch_69fbbd18c9908190928d274f8731dfa8 completed May 6, 2026, 10:13 p.m.
Created at: May 3, 2026, 4:20 p.m.