Triple

T25675528
Position Surface form Disambiguated ID Type / Status
Subject Athena E643793 entity
Predicate plotSummary P264 FINISHED
Object A conservative lawyer becomes involved with a health-obsessed family led by a young woman named Athena, whose unconventional lifestyle challenges his conventional views.
Athena is the central character in a comedic narrative whose alternative, health-obsessed lifestyle and leadership of her eccentric family upend and challenge the rigid worldview of a conservative lawyer drawn into their orbit.
E1691686 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 conservative lawyer becomes involved with a health-obsessed family led by a young woman named Athena, whose unconventional lifestyle challenges his conventional views. | Statement: [Athena, plotSummary, A conservative lawyer becomes involved with a health-obsessed family led by a young woman named Athena, whose unconventional lifestyle challenges his conventional views.]
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 conservative lawyer becomes involved with a health-obsessed family led by a young woman named Athena, whose unconventional lifestyle challenges his conventional views.
Triple: [Athena, plotSummary, A conservative lawyer becomes involved with a health-obsessed family led by a young woman named Athena, whose unconventional lifestyle challenges his conventional views.]
Generated description
Athena is the central character in a comedic narrative whose alternative, health-obsessed lifestyle and leadership of her eccentric family upend and challenge the rigid worldview of a conservative lawyer drawn into their orbit.

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_69e77e7f69808190ad27df1006f6037a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fb3648848190bd3229ed424d5545 completed May 2, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10c15d396881909a0825c45463dc38 completed May 22, 2026, 8:49 p.m.
NEDg Description generation batch_6a10c1f3ae208190b3cdc518e83bbc7f completed May 22, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_6a10c2b0c540819086fe2b0fef3f76d1 completed May 22, 2026, 8:55 p.m.
Created at: April 21, 2026, 7:37 p.m.