Triple

T38628880
Position Surface form Disambiguated ID Type / Status
Subject Elmer Clifton E937391 entity
Predicate directedForStudio P6107 FINISHED
Object Poverty Row studios
Poverty Row studios were a group of low-budget, independent American film production companies active mainly from the 1920s to the 1950s, known for quickly made B-movies and genre films.
 E2278505 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: Poverty Row studios | Statement: [Elmer Clifton, directedForStudio, Poverty Row studios]
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: Poverty Row studios
Triple: [Elmer Clifton, directedForStudio, Poverty Row studios]
Generated description
Poverty Row studios were a group of low-budget, independent American film production companies active mainly from the 1920s to the 1950s, known for quickly made B-movies and genre films.

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_69f76ed5ca3c81909288f61fbf37b359 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd9994d6881908642003be9a65a05 completed May 7, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41f450fa8c819081e3ced582be9956 completed June 29, 2026, 4:28 a.m.
NEDg Description generation batch_6a41f55d6f74819085b208204dcd68dc completed June 29, 2026, 4:32 a.m.
NED2 Entity disambiguation (via description) batch_6a41f6229fb8819099ba86f2db3ae6d1 completed June 29, 2026, 4:35 a.m.
Created at: May 3, 2026, 4:32 p.m.