Triple

T1946830
Position Surface form Disambiguated ID Type / Status
Subject Big Circle Line E42071 entity
Predicate hasStation P35 FINISHED
Object Terekhovo
Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
 E244651 NE FINISHED

How this triple was built (4 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: Terekhovo | Statement: [Big Circle Line, hasStation, Terekhovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Terekhovo
Context triple: [Big Circle Line, hasStation, Terekhovo]
  • A. Skovorodino
    Skovorodino is a small town in Russia’s Far Eastern Amur Oblast, known historically as a railway junction on the Trans-Siberian Railway.
  • B. Kamyshin
    Kamyshin is a significant industrial and river port city on the Volga River in southwestern Russia.
  • C. Kolomna
    Kolomna is a historic Russian city southeast of Moscow, known for its well-preserved kremlin, medieval architecture, and traditional pastila confectionery.
  • D. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • E. Shakhovskoye
    Shakhovskoye is a rural locality in Russia known primarily as the birthplace of Soviet politician Mikhail Suslov.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Terekhovo
Triple: [Big Circle Line, hasStation, Terekhovo]
Generated description
Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Terekhovo
Target entity description: Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
  • A. Skovorodino
    Skovorodino is a small town in Russia’s Far Eastern Amur Oblast, known historically as a railway junction on the Trans-Siberian Railway.
  • B. Kamyshin
    Kamyshin is a significant industrial and river port city on the Volga River in southwestern Russia.
  • C. Kolomna
    Kolomna is a historic Russian city southeast of Moscow, known for its well-preserved kremlin, medieval architecture, and traditional pastila confectionery.
  • D. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • E. Shakhovskoye
    Shakhovskoye is a rural locality in Russia known primarily as the birthplace of Soviet politician Mikhail Suslov.
  • F. None of above. chosen

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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb32ebae881908f7541301f0198ae completed March 7, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae65254bf48190bc12fb982dfde46c completed March 9, 2026, 6:13 a.m.
NEDg Description generation batch_69ae666bd32c81909ff15201757a6c76 completed March 9, 2026, 6:19 a.m.
NED2 Entity disambiguation (via description) batch_69ae66d8ba688190a2102c00fc6231c4 completed March 9, 2026, 6:21 a.m.
Created at: March 4, 2026, 7:36 p.m.