Triple

T1916082
Position Surface form Disambiguated ID Type / Status
Subject Bundelkhand E40019 entity
Predicate traditionalCuisineItem P6863 FINISHED
Object Lapsi
Lapsi is a traditional North Indian sweet dish made from broken wheat, ghee, and sugar, commonly prepared during festivals and special occasions in regions like Bundelkhand.
 E216386 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: Lapsi | Statement: [Bundelkhand, traditionalCuisineItem, Lapsi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lapsi
Context triple: [Bundelkhand, traditionalCuisineItem, Lapsi]
  • A. Bebek
    Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
  • B. Oppum
    Oppum is a district of the German city of Krefeld in the state of North Rhine-Westphalia.
  • C. Palikir
    Palikir is the small, inland capital city of the Federated States of Micronesia, located on the island of Pohnpei in the western Pacific Ocean.
  • D. Limmat
    The Limmat is a Swiss river that flows out of Lake Zurich through the city of Zurich and continues northward until it joins the Aare.
  • E. Nelonen
    Nelonen is a prominent Finnish commercial television channel known for broadcasting a wide range of entertainment, drama, reality shows, and sports programming.
  • 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: Lapsi
Triple: [Bundelkhand, traditionalCuisineItem, Lapsi]
Generated description
Lapsi is a traditional North Indian sweet dish made from broken wheat, ghee, and sugar, commonly prepared during festivals and special occasions in regions like Bundelkhand.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lapsi
Target entity description: Lapsi is a traditional North Indian sweet dish made from broken wheat, ghee, and sugar, commonly prepared during festivals and special occasions in regions like Bundelkhand.
  • A. Bebek
    Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
  • B. Oppum
    Oppum is a district of the German city of Krefeld in the state of North Rhine-Westphalia.
  • C. Palikir
    Palikir is the small, inland capital city of the Federated States of Micronesia, located on the island of Pohnpei in the western Pacific Ocean.
  • D. Limmat
    The Limmat is a Swiss river that flows out of Lake Zurich through the city of Zurich and continues northward until it joins the Aare.
  • E. Nelonen
    Nelonen is a prominent Finnish commercial television channel known for broadcasting a wide range of entertainment, drama, reality shows, and sports programming.
  • 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1e517e8819086e4bf5a305aeb25 completed March 7, 2026, 5:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3da81308190a49844a8ac2997da completed March 8, 2026, 10:10 p.m.
NEDg Description generation batch_69adf5d259488190ad105f0083577ecc completed March 8, 2026, 10:18 p.m.
NED2 Entity disambiguation (via description) batch_69adf6264d148190be0daef2be7f920d completed March 8, 2026, 10:20 p.m.
Created at: March 4, 2026, 7:35 p.m.