Triple

T12191838
Position Surface form Disambiguated ID Type / Status
Subject Red Star Stadium E290481 entity
Predicate hasNickName P39 FINISHED
Object Marakana
Marakana is the popular nickname for Red Star Stadium, the iconic football arena in Belgrade, Serbia, known for its intense atmosphere and passionate supporters.
 E970299 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: Marakana | Statement: [Red Star Stadium, hasNickName, Marakana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marakana
Context triple: [Red Star Stadium, hasNickName, Marakana]
  • A. Malakula
    Malakula is one of the largest and most culturally diverse islands of Vanuatu, known for its many distinct languages and traditional customs.
  • B. Negaraku
    Negaraku is the national anthem of Malaysia, symbolizing the country's sovereignty and unity.
  • C. Matanao
    Matanao is a municipality located in the province of Davao del Sur in the Philippines, known primarily as an agricultural community.
  • D. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • E. Makadara
    Makadara is a residential and commercial neighborhood in Nairobi, Kenya, known for its dense population, vibrant local markets, and mix of low- to middle-income housing.
  • 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: Marakana
Triple: [Red Star Stadium, hasNickName, Marakana]
Generated description
Marakana is the popular nickname for Red Star Stadium, the iconic football arena in Belgrade, Serbia, known for its intense atmosphere and passionate supporters.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marakana
Target entity description: Marakana is the popular nickname for Red Star Stadium, the iconic football arena in Belgrade, Serbia, known for its intense atmosphere and passionate supporters.
  • A. Malakula
    Malakula is one of the largest and most culturally diverse islands of Vanuatu, known for its many distinct languages and traditional customs.
  • B. Negaraku
    Negaraku is the national anthem of Malaysia, symbolizing the country's sovereignty and unity.
  • C. Matanao
    Matanao is a municipality located in the province of Davao del Sur in the Philippines, known primarily as an agricultural community.
  • D. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • E. Makadara
    Makadara is a residential and commercial neighborhood in Nairobi, Kenya, known for its dense population, vibrant local markets, and mix of low- to middle-income housing.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c54a4648190ad0f84c229534155 completed April 10, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a8d24508190b0a60ca76d775b1e completed May 2, 2026, 2:30 p.m.
NEDg Description generation batch_69f60c9276d0819086b5f7712fe8d6e6 completed May 2, 2026, 2:39 p.m.
NED2 Entity disambiguation (via description) batch_69f60d4889d48190b2dfda8a0978cc72 completed May 2, 2026, 2:42 p.m.
Created at: April 8, 2026, 9:50 p.m.