Triple

T28062673
Position Surface form Disambiguated ID Type / Status
Subject Victor Alvarez E709156 entity
Predicate appearsIn P795 FINISHED
Object One Day at a Time
One Day at a Time is an American sitcom that follows the everyday struggles and growth of a single mother and her family, originally airing in the 1970s–80s and later reimagined in a modern reboot.
 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, appearsIn, 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, appearsIn, One Day at a Time]
Generated description
One Day at a Time is an American sitcom that follows the everyday struggles and growth of a single mother and her family, originally airing in the 1970s–80s and later reimagined in a modern reboot.

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_6a15b8c3419081909a42cf527aaad150 completed May 26, 2026, 3:14 p.m.
NEDg Description generation batch_6a15be1faeac8190935afd57ad649725 completed May 26, 2026, 3:37 p.m.
NED2 Entity disambiguation (via description) batch_6a15be9e1bf88190b52bbc84da6ab0c3 completed May 26, 2026, 3:39 p.m.
Created at: April 27, 2026, 8:40 p.m.