Triple

T6015621
Position Surface form Disambiguated ID Type / Status
Subject Southern Transdanubia E133942 entity
Predicate containsCity P294 FINISHED
Object Szekszárd
Szekszárd is a historic Hungarian town renowned as one of the country’s leading red wine regions and the administrative center of Tolna County.
 E587450 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: Szekszárd | Statement: [Southern Transdanubia, containsCity, Szekszárd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Szekszárd
Context triple: [Southern Transdanubia, containsCity, Szekszárd]
  • A. Veszprém
    Veszprém is a historic city in western Hungary known for its medieval castle district and role as a regional cultural and administrative center.
  • B. 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.
  • 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. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • 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: Szekszárd
Triple: [Southern Transdanubia, containsCity, Szekszárd]
Generated description
Szekszárd is a historic Hungarian town renowned as one of the country’s leading red wine regions and the administrative center of Tolna County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Szekszárd
Target entity description: Szekszárd is a historic Hungarian town renowned as one of the country’s leading red wine regions and the administrative center of Tolna County.
  • A. Veszprém
    Veszprém is a historic city in western Hungary known for its medieval castle district and role as a regional cultural and administrative center.
  • B. 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.
  • 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. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • 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_69c0087361a48190905c6b55969852b8 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f80ec108190ae9711727debb061 completed March 22, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62cf2edd48190b3d5f6bf27075fed completed March 27, 2026, 7:08 a.m.
NEDg Description generation batch_69c62dcb9e1481909fb357f2b010bc19 completed March 27, 2026, 7:12 a.m.
NED2 Entity disambiguation (via description) batch_69c62e33354481908a6a9af5c245f307 completed March 27, 2026, 7:13 a.m.
Created at: March 22, 2026, 4:06 p.m.