Triple

T34097762
Position Surface form Disambiguated ID Type / Status
Subject Are You the One? E874482 entity
Predicate hasSpinOffOrRelatedShow P45612 FINISHED
Object Are You the One? Second Chances
Are You the One? Second Chances is a reality TV spin-off series that follows previously matched couples from the original show as they compete in challenges to test their relationships and win prize money.
E275669 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: Are You the One? Second Chances | Statement: [Are You the One?, hasSpinOffOrRelatedShow, Are You the One? Second Chances]
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: Are You the One? Second Chances
Triple: [Are You the One?, hasSpinOffOrRelatedShow, Are You the One? Second Chances]
Generated description
Are You the One? Second Chances is a reality TV spin-off series that follows previously matched couples from the original show as they compete in challenges to test their relationships and win prize money.

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_69f349a735208190a1dbfb1c2a121059 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70c6153e48190879589fa9eab790f completed May 3, 2026, 8:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36ae6083c88190bbbc3f002efba9e2 completed June 20, 2026, 3:14 p.m.
NEDg Description generation batch_6a36aef70cac81909864ca6c04cbfa2a completed June 20, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_6a36afc47fc4819097fd115ba24b55dc completed June 20, 2026, 3:20 p.m.
Created at: May 1, 2026, 1:53 a.m.