Triple

T3335891
Position Surface form Disambiguated ID Type / Status
Subject Buda E70138 entity
Predicate hasPart P35 FINISHED
Object Krisztinaváros
Krisztinaváros is a historic neighborhood in Budapest’s Buda side, known for its 19th-century architecture, cultural landmarks, and proximity to the Castle District.
E349576 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: Krisztinaváros | Statement: [Buda, hasPart, Krisztinaváros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krisztinaváros
Context triple: [Buda, hasPart, Krisztinaváros]
  • A. Tiszaújváros
    Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
  • B. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • C. Szentendre
    Szentendre is a picturesque riverside town near Budapest in Hungary, known for its baroque architecture, art galleries, and vibrant cultural scene.
  • D. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • E. Sátoraljaújhely
    Sátoraljaújhely is a historic town in northeastern Hungary near the Slovak border, known for its wine region, cultural heritage, and scenic Zemplén Mountains setting.
  • 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: Krisztinaváros
Triple: [Buda, hasPart, Krisztinaváros]
Generated description
Krisztinaváros is a historic neighborhood in Budapest’s Buda side, known for its 19th-century architecture, cultural landmarks, and proximity to the Castle District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Krisztinaváros
Target entity description: Krisztinaváros is a historic neighborhood in Budapest’s Buda side, known for its 19th-century architecture, cultural landmarks, and proximity to the Castle District.
  • A. Tiszaújváros
    Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
  • B. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • C. Szentendre
    Szentendre is a picturesque riverside town near Budapest in Hungary, known for its baroque architecture, art galleries, and vibrant cultural scene.
  • D. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • E. Sátoraljaújhely
    Sátoraljaújhely is a historic town in northeastern Hungary near the Slovak border, known for its wine region, cultural heritage, and scenic Zemplén Mountains setting.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb197bd0481909a5cf7eab386e176 completed March 8, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a885d148190a101ce50d5d87f53 completed March 12, 2026, 7:56 p.m.
NEDg Description generation batch_69b31c393f20819098d5761372d6a980 completed March 12, 2026, 8:04 p.m.
NED2 Entity disambiguation (via description) batch_69b3206be2748190874560701dc1ed18 completed March 12, 2026, 8:22 p.m.
Created at: March 8, 2026, 3:12 p.m.