Triple

T33510877
Position Surface form Disambiguated ID Type / Status
Subject Roller Boogie E858238 entity
Predicate starring P1507 FINISHED
Object Roger Perry
Roger Perry was an American character actor known for his numerous television and film roles from the 1950s through the 1990s.
E2058446 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: Roger Perry | Statement: [Roller Boogie, starring, Roger Perry]
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: Roger Perry
Triple: [Roller Boogie, starring, Roger Perry]
Generated description
Roger Perry was an American character actor known for his numerous television and film roles from the 1950s through the 1990s.

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_69f3497721848190978fbee5e0a526f8 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f66eb2b48190b551b1c8b1172042 completed May 3, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35afc542e08190bf8343627255544e completed June 19, 2026, 9:08 p.m.
NEDg Description generation batch_6a35b38fe2148190a4a285777ac01368 completed June 19, 2026, 9:24 p.m.
NED2 Entity disambiguation (via description) batch_6a35b3fe791c8190a8b52cea40f31273 completed June 19, 2026, 9:26 p.m.
Created at: May 1, 2026, 1:38 a.m.