Triple

T29798907
Position Surface form Disambiguated ID Type / Status
Subject Wadd: The Life & Times of John C. Holmes E756633 entity
Predicate featuresInterviewWith P17405 FINISHED
Object Annette Haven
Annette Haven is an American former adult film actress prominent in the 1970s and 1980s, known for her performances in the Golden Age of Porn.
E1890705 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: Annette Haven | Statement: [Wadd: The Life & Times of John C. Holmes, featuresInterviewWith, Annette Haven]
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: Annette Haven
Triple: [Wadd: The Life & Times of John C. Holmes, featuresInterviewWith, Annette Haven]
Generated description
Annette Haven is an American former adult film actress prominent in the 1970s and 1980s, known for her performances in the Golden Age of Porn.

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_69f22454583081908927516cb9938d1d completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f674e861f08190a85ab46799e50c74 completed May 2, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2713fe08f88190b9c467f940d0c8bb completed June 8, 2026, 7:11 p.m.
NEDg Description generation batch_6a27150eabc08190b332d916627afedf completed June 8, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_6a2716b75fbc81909a83533f33033a4b completed June 8, 2026, 7:23 p.m.
Created at: April 29, 2026, 5:17 p.m.