Triple

T35478172
Position Surface form Disambiguated ID Type / Status
Subject Justin Moorhouse E1025392 entity
Predicate notableWork P4 FINISHED
Object The Premier League Show
The Premier League Show is a British television program focused on in-depth coverage, analysis, and features about England’s top-flight football league.
E2142514 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: The Premier League Show | Statement: [Justin Moorhouse, notableWork, The Premier League Show]
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: The Premier League Show
Triple: [Justin Moorhouse, notableWork, The Premier League Show]
Generated description
The Premier League Show is a British television program focused on in-depth coverage, analysis, and features about England’s top-flight football league.

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_69f76dfadba0819083456aadcd6864ea completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f796ea63e481909aee158f63640352 completed May 3, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38403daba0819096a88a4b90ae4fe5 completed June 21, 2026, 7:49 p.m.
NEDg Description generation batch_6a38412b825c8190bb041dcf4f238c3e completed June 21, 2026, 7:53 p.m.
NED2 Entity disambiguation (via description) batch_6a38425594c481908679cd38b14e31c8 completed June 21, 2026, 7:58 p.m.
Created at: May 3, 2026, 4:04 p.m.