Triple

T27619910
Position Surface form Disambiguated ID Type / Status
Subject King or Queen of Comedy E700547 entity
Predicate alsoKnownAs P39 FINISHED
Object People’s Choice Award: King or Queen of Comedy
The People’s Choice Award: King or Queen of Comedy is a fan-voted honor recognizing the most popular comedic performer in a given year.
E1779425 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: People’s Choice Award: King or Queen of Comedy | Statement: [King or Queen of Comedy, alsoKnownAs, People’s Choice Award: King or Queen of Comedy]
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: People’s Choice Award: King or Queen of Comedy
Triple: [King or Queen of Comedy, alsoKnownAs, People’s Choice Award: King or Queen of Comedy]
Generated description
The People’s Choice Award: King or Queen of Comedy is a fan-voted honor recognizing the most popular comedic performer in a given year.

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_69ef6a4f1d9c8190b0705acda054368d completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f630dbc9b08190aa253e2b85f2f39a completed May 2, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0f3755c81909a7f2a44140676ff completed May 24, 2026, 10:20 a.m.
NEDg Description generation batch_6a12d16a912881909edf8e2359b34503 completed May 24, 2026, 10:22 a.m.
NED2 Entity disambiguation (via description) batch_6a12d21a403881908ba269eefc7c160b completed May 24, 2026, 10:25 a.m.
Created at: April 27, 2026, 2:14 p.m.