Triple

T9786191
Position Surface form Disambiguated ID Type / Status
Subject TurkishCuisine E237494 entity
Predicate usesIngredient P12771 FINISHED
Object Bulgur
Bulgur is a whole grain food made from cracked, parboiled wheat, commonly used in Middle Eastern and Mediterranean dishes like pilafs, salads, and stuffings.
 E820767 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: Bulgur | Statement: [TurkishCuisine, usesIngredient, Bulgur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bulgur
Context triple: [TurkishCuisine, usesIngredient, Bulgur]
  • A. Millet
    Millet is a common French surname borne by several notable figures, including artists and sculptors.
  • B. Dinkel
    Dinkel is a small river in the eastern Netherlands and western Germany, known for flowing through the Twente region and its relatively unspoiled natural landscapes.
  • C. Farino
    Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
  • D. Emmer
    Emmer is a river in northwestern Germany that flows through Lower Saxony and North Rhine-Westphalia before joining the Weser.
  • E. Kasha
    Kasha is a feminine given name used in various cultures, often as a diminutive or variant of names like Katarzyna or Kasia.
  • 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: Bulgur
Triple: [TurkishCuisine, usesIngredient, Bulgur]
Generated description
Bulgur is a whole grain food made from cracked, parboiled wheat, commonly used in Middle Eastern and Mediterranean dishes like pilafs, salads, and stuffings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bulgur
Target entity description: Bulgur is a whole grain food made from cracked, parboiled wheat, commonly used in Middle Eastern and Mediterranean dishes like pilafs, salads, and stuffings.
  • A. Millet
    Millet is a common French surname borne by several notable figures, including artists and sculptors.
  • B. Dinkel
    Dinkel is a small river in the eastern Netherlands and western Germany, known for flowing through the Twente region and its relatively unspoiled natural landscapes.
  • C. Farino
    Farino is a small rural commune in the South Province of New Caledonia, known for its lush forests and eco-tourism activities.
  • D. Emmer
    Emmer is a river in northwestern Germany that flows through Lower Saxony and North Rhine-Westphalia before joining the Weser.
  • E. Kasha
    Kasha is a feminine given name used in various cultures, often as a diminutive or variant of names like Katarzyna or Kasia.
  • 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.