Triple

T9786170
Position Surface form Disambiguated ID Type / Status
Subject TurkishCuisine E237494 entity
Predicate typicalDessert P26231 FINISHED
Object Tulumba
Tulumba is a popular deep-fried, syrup-soaked pastry dessert found across Turkey and other parts of the Middle East and the Balkans.
E820761 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: Tulumba | Statement: [TurkishCuisine, typicalDessert, Tulumba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tulumba
Context triple: [TurkishCuisine, typicalDessert, Tulumba]
  • A. Taquara
    Taquara is a residential neighborhood in the West Zone of Rio de Janeiro, Brazil, known for its mix of urban development and remaining green areas.
  • B. Otumba
    Otumba is a town in central Mexico historically notable as the site of the Battle of Otumba during the Spanish conquest.
  • C. Pilón
    Pilón is a coastal town and municipality in southeastern Cuba known for its fishing activities and proximity to the Sierra Maestra mountains.
  • D. Tumeremo
    Tumeremo is a mining town in southeastern Venezuela known for its gold deposits and location within Bolívar State.
  • E. Pilla
    Pilla is an Italian surname most notably associated with Franca Pilla, the wife of former Italian President Carlo Azeglio Ciampi.
  • 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: Tulumba
Triple: [TurkishCuisine, typicalDessert, Tulumba]
Generated description
Tulumba is a popular deep-fried, syrup-soaked pastry dessert found across Turkey and other parts of the Middle East and the Balkans.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tulumba
Target entity description: Tulumba is a popular deep-fried, syrup-soaked pastry dessert found across Turkey and other parts of the Middle East and the Balkans.
  • A. Taquara
    Taquara is a residential neighborhood in the West Zone of Rio de Janeiro, Brazil, known for its mix of urban development and remaining green areas.
  • B. Otumba
    Otumba is a town in central Mexico historically notable as the site of the Battle of Otumba during the Spanish conquest.
  • C. Pilón
    Pilón is a coastal town and municipality in southeastern Cuba known for its fishing activities and proximity to the Sierra Maestra mountains.
  • D. Tumeremo
    Tumeremo is a mining town in southeastern Venezuela known for its gold deposits and location within Bolívar State.
  • E. Pilla
    Pilla is an Italian surname most notably associated with Franca Pilla, the wife of former Italian President Carlo Azeglio Ciampi.
  • 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_69ca84da927881909bda80caecad6010 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda2107f688190b2cab1509c508319 completed April 1, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c4235ae88190aefaa6d9b63031e0 completed April 5, 2026, 2:08 a.m.
NEDg Description generation batch_69d1c477c9c48190b08f4871955d4450 completed April 5, 2026, 2:09 a.m.
NED2 Entity disambiguation (via description) batch_69d1c520d3988190b7735f6d16e78ab5 completed April 5, 2026, 2:12 a.m.
Created at: March 30, 2026, 8:27 p.m.