Triple

T34777918
Position Surface form Disambiguated ID Type / Status
Subject Jane Kennedy E1002551 entity
Predicate notableWork P4 FINISHED
Object Fabulous Food Minus the Boombah
Fabulous Food Minus the Boombah is a popular healthy cookbook by Australian comedian and presenter Jane Kennedy, focusing on lighter, everyday recipes without sacrificing flavor.
E2112387 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: Fabulous Food Minus the Boombah | Statement: [Jane Kennedy, notableWork, Fabulous Food Minus the Boombah]
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: Fabulous Food Minus the Boombah
Triple: [Jane Kennedy, notableWork, Fabulous Food Minus the Boombah]
Generated description
Fabulous Food Minus the Boombah is a popular healthy cookbook by Australian comedian and presenter Jane Kennedy, focusing on lighter, everyday recipes without sacrificing flavor.

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_69f76db30a108190bb57ca95b873e5bb completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a402d848190a07c609fa54b62bf completed May 3, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a376641152c81908bed99deaef88a23 completed June 21, 2026, 4:19 a.m.
NEDg Description generation batch_6a37670a06888190a62323cca2fb2708 completed June 21, 2026, 4:22 a.m.
NED2 Entity disambiguation (via description) batch_6a376902593881908e9bdcd5d3231026 completed June 21, 2026, 4:30 a.m.
Created at: May 3, 2026, 3:59 p.m.