Triple

T26987693
Position Surface form Disambiguated ID Type / Status
Subject G.I. Joe: The Movie E679777 entity
Predicate voiceCastMember P9616 FINISHED
Object Arthur Burghardt
Arthur Burghardt is an American actor and voice actor best known for voicing characters such as Destro in the G.I. Joe franchise and Devastator in The Transformers.
E1749870 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: Arthur Burghardt | Statement: [G.I. Joe: The Movie, voiceCastMember, Arthur Burghardt]
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: Arthur Burghardt
Triple: [G.I. Joe: The Movie, voiceCastMember, Arthur Burghardt]
Generated description
Arthur Burghardt is an American actor and voice actor best known for voicing characters such as Destro in the G.I. Joe franchise and Devastator in The Transformers.

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_69eeeb5138ac8190b3c273ddc659a54f completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f6215b9bc881909614a84c9f0dc499 completed May 2, 2026, 4:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1229b43e5481909dfb4445dc00d07b completed May 23, 2026, 10:27 p.m.
NEDg Description generation batch_6a122a3a3b3c8190ab41feb5652546bb completed May 23, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a122add10688190aa06ce1d690c1867 completed May 23, 2026, 10:31 p.m.
Created at: April 27, 2026, 6:49 a.m.