Triple

T23662260
Position Surface form Disambiguated ID Type / Status
Subject Call Your Mother E584481 entity
Predicate mainCharacter P1183 FINISHED
Object Jean Raines
Jean Raines is the overbearing yet loving mother at the center of the sitcom "Call Your Mother," whose decision to reconnect with her grown children drives the show's comedic and emotional storylines.
E1598043 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: Jean Raines | Statement: [Call Your Mother, mainCharacter, Jean Raines]
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: Jean Raines
Triple: [Call Your Mother, mainCharacter, Jean Raines]
Generated description
Jean Raines is the overbearing yet loving mother at the center of the sitcom "Call Your Mother," whose decision to reconnect with her grown children drives the show's comedic and emotional storylines.

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_69e248ffc0888190ae23c4731eb8b7ac completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b4094c448190be12402422451e89 completed April 29, 2026, 7:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f45b494208190994e3a093bd4b5a7 completed May 21, 2026, 5:49 p.m.
NEDg Description generation batch_6a0f46fb66dc8190bdbca0134bc7d00a completed May 21, 2026, 5:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0f4ace63e0819081e9c2c0adf77abf completed May 21, 2026, 6:11 p.m.
Created at: April 17, 2026, 6:50 p.m.