Triple

T38439442
Position Surface form Disambiguated ID Type / Status
Subject Honey Bruce E906446 entity
Predicate alsoKnownAs P39 FINISHED
Object Harriett Jolliff
Harriett Jolliff was the birth name of Honey Bruce, an American stripper and showgirl best known as the wife of controversial comedian Lenny Bruce.
E2281080 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: Harriett Jolliff | Statement: [Honey Bruce, alsoKnownAs, Harriett Jolliff]
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: Harriett Jolliff
Triple: [Honey Bruce, alsoKnownAs, Harriett Jolliff]
Generated description
Harriett Jolliff was the birth name of Honey Bruce, an American stripper and showgirl best known as the wife of controversial comedian Lenny Bruce.

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_69f76e72878c8190a692836c8b01b58b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fccdd55f848190bf09df92e7e45ad7 completed May 7, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4205ac04708190a077c4e6076450c8 completed June 29, 2026, 5:42 a.m.
NEDg Description generation batch_6a42061f71dc8190aeca79f1cf65aff2 completed June 29, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_6a42067af3e08190856a4cd5a991c9b0 completed June 29, 2026, 5:45 a.m.
Created at: May 3, 2026, 4:31 p.m.