Triple

T25015573
Position Surface form Disambiguated ID Type / Status
Subject Robert Cletus Driscoll E626120 entity
Predicate notableWork P4 FINISHED
Object The Window
"The Window" is a 1949 American film noir thriller, based on Cornell Woolrich’s short story "The Boy Cried Murder," about a young boy who witnesses a murder but struggles to convince adults that the crime really occurred.
E547952 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: The Window | Statement: [Robert Cletus Driscoll, notableWork, The Window]
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: The Window
Triple: [Robert Cletus Driscoll, notableWork, The Window]
Generated description
"The Window" is a 1949 American film noir thriller, based on Cornell Woolrich’s short story "The Boy Cried Murder," about a young boy who witnesses a murder but struggles to convince adults that the crime really occurred.

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_69e2ff27755881908490178e83701160 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44ba594a08190beb28ace68e1e120 completed May 1, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048b061f081908f53bd6ad3927967 completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a104947e5c08190adf11246162fa1fb completed May 22, 2026, 12:17 p.m.
NED2 Entity disambiguation (via description) batch_6a104a50e59c81908e576aeb2cebc1c5 completed May 22, 2026, 12:21 p.m.
Created at: April 18, 2026, 6:06 a.m.