Triple

T25207014
Position Surface form Disambiguated ID Type / Status
Subject Kumar Dharmasena E631279 entity
Predicate awardReceived P11 FINISHED
Object ICC Umpire of the Year
The ICC Umpire of the Year is an annual cricket award presented by the International Cricket Council to recognize the best-performing on-field umpire in international matches.
E546264 NE FINISHED

How this triple was built (2 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: ICC Umpire of the Year | Statement: [Kumar Dharmasena, awardReceived, ICC Umpire of the Year]
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: ICC Umpire of the Year
Triple: [Kumar Dharmasena, awardReceived, ICC Umpire of the Year]
Generated description
The ICC Umpire of the Year is an annual cricket award presented by the International Cricket Council to recognize the best-performing on-field umpire in international matches.

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_69e75a8b86c4819089eda22c843b739f completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f474bce13c8190bcdd22cdd70490b5 completed May 1, 2026, 9:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d3094b08190b69af586b21f9ee6 completed May 22, 2026, 1:42 p.m.
NEDg Description generation batch_6a105e53f9bc8190a4b0929a68d83b0a completed May 22, 2026, 1:47 p.m.
NED2 Entity disambiguation (via description) batch_6a105edf54888190a3b77f63eb867749 completed May 22, 2026, 1:49 p.m.
Created at: April 21, 2026, 12:52 p.m.