Triple

T34368689
Position Surface form Disambiguated ID Type / Status
Subject Passionate Summer E882090 entity
Predicate starredActor P5563 FINISHED
Object John Boxer
John Boxer was a British character actor known for his supporting roles in mid-20th-century films and television.
E2093205 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: John Boxer | Statement: [Passionate Summer, starredActor, John Boxer]
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: John Boxer
Triple: [Passionate Summer, starredActor, John Boxer]
Generated description
John Boxer was a British character actor known for his supporting roles in mid-20th-century films and television.

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_69f349be5c9c81908dc726ae1f4c68f2 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7184e76148190bbbb9ea73c366a95 completed May 3, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3704ae23b881908d28cc58c0b8dd64 completed June 20, 2026, 9:22 p.m.
NEDg Description generation batch_6a3705a276b08190ad366c805fc6d4da completed June 20, 2026, 9:26 p.m.
NED2 Entity disambiguation (via description) batch_6a370623291481909be4c2276969d415 completed June 20, 2026, 9:29 p.m.
Created at: May 1, 2026, 1:58 a.m.