Triple

T27808213
Position Surface form Disambiguated ID Type / Status
Subject Madea film series E702447 entity
Predicate hasPart P35 FINISHED
Object A Madea Homecoming
A Madea Homecoming is a 2022 comedy film written, directed by, and starring Tyler Perry, featuring his iconic character Madea navigating family drama and generational clashes during a college graduation celebration.
E1812530 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: A Madea Homecoming | Statement: [Madea film series, hasPart, A Madea Homecoming]
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: A Madea Homecoming
Triple: [Madea film series, hasPart, A Madea Homecoming]
Generated description
A Madea Homecoming is a 2022 comedy film written, directed by, and starring Tyler Perry, featuring his iconic character Madea navigating family drama and generational clashes during a college graduation celebration.

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_69ef840a16748190926719ab96120bae completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6383ce68881908329ecd6b518e1b0 completed May 2, 2026, 5:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606f112a88190971e8553898f407c completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a161404f5908190993589611f152cd1 completed May 26, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_6a1616734eac8190947663ebe6c3d478 completed May 26, 2026, 9:53 p.m.
Created at: April 27, 2026, 5:40 p.m.