Triple

T20150636
Position Surface form Disambiguated ID Type / Status
Subject Andhra cuisine E491424 entity
Predicate hasDish P17589 FINISHED
Object upma pesarattu
Upma pesarattu is a popular Andhra breakfast dish consisting of a thin green gram dosa wrapped around a filling of savory semolina upma.
 E1415221 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: upma pesarattu | Statement: [Andhra cuisine, hasDish, upma pesarattu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: upma pesarattu
Context triple: [Andhra cuisine, hasDish, upma pesarattu]
  • A. UP
    UP is the standard reporting mark used to identify rail equipment owned or operated by the Union Pacific Railroad in North America.
  • B. UP
    UP was a major South African political party that dominated the country’s politics for much of the mid-20th century before being displaced by the National Party.
  • C. UP
    UP is the commonly used abbreviation for the University of Primorska, a public university based in the coastal region of Slovenia.
  • D. UP
    UP is a leading South African public research university located in Pretoria, known for its comprehensive range of academic programs and strong research output.
  • E. UP
    UP is the official vehicle registration code assigned to Sri Lanka’s Uva Province.
  • 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: upma pesarattu
Triple: [Andhra cuisine, hasDish, upma pesarattu]
Generated description
Upma pesarattu is a popular Andhra breakfast dish consisting of a thin green gram dosa wrapped around a filling of savory semolina upma.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: upma pesarattu
Target entity description: Upma pesarattu is a popular Andhra breakfast dish consisting of a thin green gram dosa wrapped around a filling of savory semolina upma.
  • A. UP
    UP is the standard reporting mark used to identify rail equipment owned or operated by the Union Pacific Railroad in North America.
  • B. UP
    UP was a major South African political party that dominated the country’s politics for much of the mid-20th century before being displaced by the National Party.
  • C. UP
    UP is a leading South African public research university located in Pretoria, known for its comprehensive range of academic programs and strong research output.
  • D. UP
    UP is the official vehicle registration code assigned to Sri Lanka’s Uva Province.
  • E. UP
    UP is the commonly used abbreviation for the University of Primorska, a public university based in the coastal region of Slovenia.
  • 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667a1c5848190975b17ab07251f8b completed April 20, 2026, 5:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08346f7b708190b006704558b25a67 completed May 16, 2026, 9:10 a.m.
NEDg Description generation batch_6a08357acba08190be9fcedf1ea0f19d completed May 16, 2026, 9:14 a.m.
NED2 Entity disambiguation (via description) batch_6a0836a5cfdc81908806d83acd257acd completed May 16, 2026, 9:19 a.m.
Created at: April 11, 2026, 11:33 p.m.