Triple

T26195154
Position Surface form Disambiguated ID Type / Status
Subject Hot for Teacher E655076 entity
Predicate musicVideoDirector P4911 FINISHED
Object Pete Angelus
Pete Angelus is an American music video director and artist manager best known for his long association with Van Halen and David Lee Roth, helping shape their visual style and stage productions.
E1713429 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: Pete Angelus | Statement: [Hot for Teacher, musicVideoDirector, Pete Angelus]
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: Pete Angelus
Triple: [Hot for Teacher, musicVideoDirector, Pete Angelus]
Generated description
Pete Angelus is an American music video director and artist manager best known for his long association with Van Halen and David Lee Roth, helping shape their visual style and stage productions.

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_69ee5b48236c81908fe385b6afc4f60b completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60ca50d0081909d146f3c697227aa completed May 2, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11857e8e108190a14a25356741c0d6 completed May 23, 2026, 10:46 a.m.
NEDg Description generation batch_6a11861e622c8190a73ab247d696435a completed May 23, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a1186c04c2c8190a5e70c9d9a5cbeb8 completed May 23, 2026, 10:51 a.m.
Created at: April 26, 2026, 8:46 p.m.