Triple

T6192572
Position Surface form Disambiguated ID Type / Status
Subject national road DK7 (Zakopianka corridor) E138429 entity
Predicate alsoKnownAs P39 FINISHED
Object Zakopianka
Zakopianka is a major Polish road corridor connecting Kraków with the mountain resort town of Zakopane, serving as a primary route to the Tatra Mountains.
E575213 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: Zakopianka | Statement: [national road DK7 (Zakopianka corridor), alsoKnownAs, Zakopianka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zakopianka
Context triple: [national road DK7 (Zakopianka corridor), alsoKnownAs, Zakopianka]
  • A. Vidnoye
    Vidnoye is a small town in Moscow Oblast, Russia, functioning largely as a residential and industrial satellite of Moscow.
  • B. Kuzminki
    Kuzminki is a Moscow Metro station on the Tagansko–Krasnopresnenskaya Line serving the Kuzminki District in southeastern Moscow.
  • C. Chardzhev
    Chardzhev is the former name of the city now known as Turkmenabat, a major urban center in eastern Turkmenistan.
  • D. Zolotonosha
    Zolotonosha is a historic town in central Ukraine, located in the Cherkasy region on the banks of the Zolotonoshka River.
  • E. Koropi
    Koropi is a town in the Athens metropolitan area of Greece, known as the seat of the municipality of Kropia and a local hub in the Mesogeia plain.
  • 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: Zakopianka
Triple: [national road DK7 (Zakopianka corridor), alsoKnownAs, Zakopianka]
Generated description
Zakopianka is a major Polish road corridor connecting Kraków with the mountain resort town of Zakopane, serving as a primary route to the Tatra Mountains.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zakopianka
Target entity description: Zakopianka is a major Polish road corridor connecting Kraków with the mountain resort town of Zakopane, serving as a primary route to the Tatra Mountains.
  • A. Vidnoye
    Vidnoye is a small town in Moscow Oblast, Russia, functioning largely as a residential and industrial satellite of Moscow.
  • B. Kuzminki
    Kuzminki is a Moscow Metro station on the Tagansko–Krasnopresnenskaya Line serving the Kuzminki District in southeastern Moscow.
  • C. Chardzhev
    Chardzhev is the former name of the city now known as Turkmenabat, a major urban center in eastern Turkmenistan.
  • D. Zolotonosha
    Zolotonosha is a historic town in central Ukraine, located in the Cherkasy region on the banks of the Zolotonoshka River.
  • E. Koropi
    Koropi is a town in the Athens metropolitan area of Greece, known as the seat of the municipality of Kropia and a local hub in the Mesogeia plain.
  • 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_69c008ab9b3081908a11b2c744838435 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06241977c81909ab8486f5aa30be0 completed March 22, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16f1403888190b558a43998fa5d05 completed March 23, 2026, 4:49 p.m.
NEDg Description generation batch_69c1e2a4ec088190bf7a7359a9f86645 completed March 24, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_69c1e3323f788190a8cc4c870fef1d2b completed March 24, 2026, 1:04 a.m.
Created at: March 22, 2026, 4:19 p.m.