Triple

T28062674
Position Surface form Disambiguated ID Type / Status
Subject Victor Alvarez E709156 entity
Predicate workOfFiction P15757 FINISHED
Object One Day at a Time
One Day at a Time is an American sitcom, originally created by Norman Lear, that follows a single mother and her family as they navigate everyday life with humor and heart.
 E32396 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: One Day at a Time | Statement: [Victor Alvarez, workOfFiction, One Day at a Time]
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: One Day at a Time
Triple: [Victor Alvarez, workOfFiction, One Day at a Time]
Generated description
One Day at a Time is an American sitcom, originally created by Norman Lear, that follows a single mother and her family as they navigate everyday life with humor and heart.

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_69ef9b6eb6d88190a3fea236eb0f7bed completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f64018804c81909397f6bcf1ab0dea completed May 2, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15d78ec1d8819088cbfa1ee9897a60 completed May 26, 2026, 5:25 p.m.
NEDg Description generation batch_6a15db1a4ac0819094b2b299c3df5516 completed May 26, 2026, 5:40 p.m.
NED2 Entity disambiguation (via description) batch_6a15dbc8593c81908624b135c3a72029 completed May 26, 2026, 5:43 p.m.
Created at: April 27, 2026, 8:40 p.m.