Triple

T33695272
Position Surface form Disambiguated ID Type / Status
Subject The Lucie Arnaz Show E863286 entity
Predicate characterName P36851 FINISHED
Object Dr. Jane Lucas
Dr. Jane Lucas is the fictional lead character, a talk-show host and psychologist, portrayed by Lucie Arnaz in the short-lived 1980s sitcom "The Lucie Arnaz Show."
E2063796 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: Dr. Jane Lucas | Statement: [The Lucie Arnaz Show, characterName, Dr. Jane Lucas]
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: Dr. Jane Lucas
Triple: [The Lucie Arnaz Show, characterName, Dr. Jane Lucas]
Generated description
Dr. Jane Lucas is the fictional lead character, a talk-show host and psychologist, portrayed by Lucie Arnaz in the short-lived 1980s sitcom "The Lucie Arnaz Show."

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_69f3498723a08190ac034339cc78eade completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fa89957881908bc50c8ce09b99b5 completed May 3, 2026, 7:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a363c99b7848190be907b8022433bd8 completed June 20, 2026, 7:09 a.m.
NEDg Description generation batch_6a364b78a0ec8190a24149ee699447b0 completed June 20, 2026, 8:12 a.m.
NED2 Entity disambiguation (via description) batch_6a364c26bdcc8190aef3486f0044cf8d completed June 20, 2026, 8:15 a.m.
Created at: May 1, 2026, 1:43 a.m.