Triple

T1184701
Position Surface form Disambiguated ID Type / Status
Subject Gorlice E25217 entity
Predicate twinTown P1072 FINISHED
Object Kaposvár
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
 E217864 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: Kaposvár | Statement: [Gorlice, twinTown, Kaposvár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kaposvár
Context triple: [Gorlice, twinTown, Kaposvár]
  • 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. Siófok
    Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
  • C. 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.
  • D. Gödöllő
    Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
  • 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: Kaposvár
Triple: [Gorlice, twinTown, Kaposvár]
Generated description
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kaposvár
Target entity description: Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy 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. Siófok
    Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
  • C. 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.
  • D. Gödöllő
    Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd39245881908766c41943dc2752 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69adfb8231ec81909d539f9bc2219619 completed March 8, 2026, 10:43 p.m.
NEDg Description generation batch_69adfbf98f508190a237a2067bf0574f completed March 8, 2026, 10:45 p.m.
NED2 Entity disambiguation (via description) batch_69adfc523d248190a1d748c7a9579d06 completed March 8, 2026, 10:46 p.m.
Created at: March 1, 2026, 7:45 p.m.