Triple

T28322370
Position Surface form Disambiguated ID Type / Status
Subject Banijay Group E717308 entity
Predicate ownsFormat P164267 FINISHED
Object Wife Swap
Wife Swap is a reality television series in which two families temporarily exchange wives or mothers to explore contrasting lifestyles, values, and household dynamics.
 E1812788 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: Wife Swap | Statement: [Banijay Group, ownsFormat, Wife Swap]
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: Wife Swap
Triple: [Banijay Group, ownsFormat, Wife Swap]
Generated description
Wife Swap is a reality television series in which two families temporarily exchange wives or mothers to explore contrasting lifestyles, values, and household dynamics.

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_69eff6e6c3b08190ad78de6ba7f04548 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64cb36ed88190973a4790577762eb completed May 2, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627b152b48190bf7043eb598dd89a completed May 26, 2026, 11:07 p.m.
NEDg Description generation batch_6a16280d37f48190a67241e83ee869eb completed May 26, 2026, 11:09 p.m.
NED2 Entity disambiguation (via description) batch_6a16286f3c708190841c6dc41328de75 completed May 26, 2026, 11:10 p.m.
Created at: April 28, 2026, 12:25 a.m.