Triple

T3508545
Position Surface form Disambiguated ID Type / Status
Subject Wolfsburg E74139 entity
Predicate twinCity P1072 FINISHED
Object Jihlava
Jihlava is a historic city in the Czech Republic, known as one of the country’s oldest mining towns and a regional cultural and administrative center.
 E365320 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: Jihlava | Statement: [Wolfsburg, twinCity, Jihlava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jihlava
Context triple: [Wolfsburg, twinCity, Jihlava]
  • A. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • B. Pardubice
    Pardubice is a city in the Czech Republic known for its ice hockey tradition, historic center, and as the hometown of legendary NHL goaltender Dominik Hašek.
  • C. Zlín
    Zlín is a city in the Czech Republic known for its modernist architecture and historical association with the Baťa shoe company.
  • D. Liberec
    Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
  • E. Jičín
    Jičín is a historic town in the Czech Republic known for its well-preserved medieval center and association with the fairy-tale character Rumcajs.
  • 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: Jihlava
Triple: [Wolfsburg, twinCity, Jihlava]
Generated description
Jihlava is a historic city in the Czech Republic, known as one of the country’s oldest mining towns and a regional cultural and administrative center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jihlava
Target entity description: Jihlava is a historic city in the Czech Republic, known as one of the country’s oldest mining towns and a regional cultural and administrative center.
  • A. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • B. Pardubice
    Pardubice is a city in the Czech Republic known for its ice hockey tradition, historic center, and as the hometown of legendary NHL goaltender Dominik Hašek.
  • C. Zlín
    Zlín is a city in the Czech Republic known for its modernist architecture and historical association with the Baťa shoe company.
  • D. Liberec
    Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
  • E. Jičín
    Jičín is a historic town in the Czech Republic known for its well-preserved medieval center and association with the fairy-tale character Rumcajs.
  • 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc0cc394819087a9b598023f4f93 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e6da490819093a5f574ff0b6b00 completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37fb14a988190aa357622773e5817 completed March 13, 2026, 3:08 a.m.
NED2 Entity disambiguation (via description) batch_69b3805e16d08190883d286a6763c079 completed March 13, 2026, 3:11 a.m.
Created at: March 8, 2026, 3:18 p.m.