Triple

T32128046
Position Surface form Disambiguated ID Type / Status
Subject Cicely Courtneidge E820555 entity
Predicate notableWork P4 FINISHED
Object The L-Shaped Room
The L-Shaped Room is a 1962 British drama film, adapted from Lynne Reid Banks’s novel, about a pregnant unmarried woman living in a shabby London boarding house.
 E236633 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 L-Shaped Room | Statement: [Cicely Courtneidge, notableWork, The L-Shaped Room]
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 L-Shaped Room
Triple: [Cicely Courtneidge, notableWork, The L-Shaped Room]
Generated description
The L-Shaped Room is a 1962 British drama film, adapted from Lynne Reid Banks’s novel, about a pregnant unmarried woman living in a shabby London boarding house.

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_69f34902d42c819083a8e6bba9a8bb9a completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b96d083881909e975a040d96c764 completed May 3, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0bc44be08190adab76bbd233699f completed June 14, 2026, 8:15 p.m.
NEDg Description generation batch_6a2f0c5dba788190b3ba409c76fcf63b completed June 14, 2026, 8:17 p.m.
NED2 Entity disambiguation (via description) batch_6a2f0cdc1b048190a34f78a36bf5bb0a completed June 14, 2026, 8:19 p.m.
Created at: May 1, 2026, 12:29 a.m.