Triple

T4495709
Position Surface form Disambiguated ID Type / Status
Subject Spišská Nová Ves E100688 entity
Predicate hasTwinTown P919 FINISHED
Object Békéscsaba
Békéscsaba is a city in southeastern Hungary known as the administrative center of Békés County and for its cultural and culinary traditions, including its famous sausage.
 E446284 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: Békéscsaba | Statement: [Spišská Nová Ves, hasTwinTown, Békéscsaba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Békéscsaba
Context triple: [Spišská Nová Ves, hasTwinTown, Békéscsaba]
  • A. Kecskemét
    Kecskemét is a city in central Hungary known for its Art Nouveau architecture, cultural institutions, and role as an administrative and economic center of the region.
  • B. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • C. Zalaegerszeg
    Zalaegerszeg is a city in western Hungary that serves as the administrative center of Zala County and a regional economic and cultural hub.
  • D. Debrecen
    Debrecen is Hungary’s second-largest city and a key cultural, economic, and educational center in the country’s eastern region.
  • E. Szeged
    Szeged is a prominent city in southern Hungary known for its university, paprika production, and distinctive Art Nouveau architecture.
  • 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: Békéscsaba
Triple: [Spišská Nová Ves, hasTwinTown, Békéscsaba]
Generated description
Békéscsaba is a city in southeastern Hungary known as the administrative center of Békés County and for its cultural and culinary traditions, including its famous sausage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Békéscsaba
Target entity description: Békéscsaba is a city in southeastern Hungary known as the administrative center of Békés County and for its cultural and culinary traditions, including its famous sausage.
  • A. Kecskemét
    Kecskemét is a city in central Hungary known for its Art Nouveau architecture, cultural institutions, and role as an administrative and economic center of the region.
  • B. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • C. Zalaegerszeg
    Zalaegerszeg is a city in western Hungary that serves as the administrative center of Zala County and a regional economic and cultural hub.
  • D. Debrecen
    Debrecen is Hungary’s second-largest city and a key cultural, economic, and educational center in the country’s eastern region.
  • E. Szeged
    Szeged is a prominent city in southern Hungary known for its university, paprika production, and distinctive Art Nouveau architecture.
  • 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_69bd43cdf15081909a4fa2585ff63b3e completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd56bde14c819091d42839a46291d0 completed March 20, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd67bfb4788190b64975b1999a8d1e completed March 20, 2026, 3:29 p.m.
NEDg Description generation batch_69bd68503f1c81909742bcf0ac356e52 completed March 20, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_69bd68b4681c8190abb170ccb054cd05 completed March 20, 2026, 3:33 p.m.
Created at: March 20, 2026, 1 p.m.