Triple

T31970516
Position Surface form Disambiguated ID Type / Status
Subject Lady in the Lake E816298 entity
Predicate portraysCharacter P1668 FINISHED
Object Audrey Totter as Adrienne Fromsett
Audrey Totter as Adrienne Fromsett is the sharp, alluring publishing executive who becomes a key figure in the mystery surrounding private detective Philip Marlowe in the 1947 film noir "Lady in the Lake."
E1985912 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: Audrey Totter as Adrienne Fromsett | Statement: [Lady in the Lake, portraysCharacter, Audrey Totter as Adrienne Fromsett]
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: Audrey Totter as Adrienne Fromsett
Triple: [Lady in the Lake, portraysCharacter, Audrey Totter as Adrienne Fromsett]
Generated description
Audrey Totter as Adrienne Fromsett is the sharp, alluring publishing executive who becomes a key figure in the mystery surrounding private detective Philip Marlowe in the 1947 film noir "Lady in the Lake."

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_69f348f5ae5481909da0247869f51955 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b307715881908825d891df5304e6 completed May 3, 2026, 2:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2eb1469464819082f12b5e0e57797d completed June 14, 2026, 1:48 p.m.
NEDg Description generation batch_6a2eb1cef8488190a83ff06da4bf30c5 completed June 14, 2026, 1:51 p.m.
NED2 Entity disambiguation (via description) batch_6a2eb25edcbc8190902aeaed0a8f9590 completed June 14, 2026, 1:53 p.m.
Created at: May 1, 2026, 12:10 a.m.