Triple

T32066064
Position Surface form Disambiguated ID Type / Status
Subject Christmas Every Day E818884 entity
Predicate hasMainCharacter P1183 FINISHED
Object Billy Jackson
Billy Jackson is the young protagonist of the holiday story "Christmas Every Day," whose wish for endless Christmases leads to humorous and ultimately enlightening consequences.
E1992319 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: Billy Jackson | Statement: [Christmas Every Day, hasMainCharacter, Billy Jackson]
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: Billy Jackson
Triple: [Christmas Every Day, hasMainCharacter, Billy Jackson]
Generated description
Billy Jackson is the young protagonist of the holiday story "Christmas Every Day," whose wish for endless Christmases leads to humorous and ultimately enlightening consequences.

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_69f348fecc088190af1470afe5a969f0 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b51f77bc8190a2641431e5f63ada completed May 3, 2026, 2:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2edde3431881909b8e7b1f0ebd7a92 completed June 14, 2026, 4:59 p.m.
NEDg Description generation batch_6a2edec9baa48190b808f231c2a917af completed June 14, 2026, 5:03 p.m.
NED2 Entity disambiguation (via description) batch_6a2eed3eb2588190bbc5e01fca423b69 completed June 14, 2026, 6:04 p.m.
Created at: May 1, 2026, 12:22 a.m.