Triple

T31111929
Position Surface form Disambiguated ID Type / Status
Subject The Last of the Knucklemen E792969 entity
Predicate notableCastMember P7010 FINISHED
Object Dennis Miller
Dennis Miller is an Australian actor known for his work in film and television, including his role in the drama "The Last of the Knucklemen."
E1946433 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: Dennis Miller | Statement: [The Last of the Knucklemen, notableCastMember, Dennis Miller]
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: Dennis Miller
Triple: [The Last of the Knucklemen, notableCastMember, Dennis Miller]
Generated description
Dennis Miller is an Australian actor known for his work in film and television, including his role in the drama "The Last of the Knucklemen."

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_69f224cfd5d881908ec6447bc321cd58 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f696e6f5888190bf13a6f937d1c1de completed May 3, 2026, 12:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2938b4eab88190aa6ec61c960be48e completed June 10, 2026, 10:13 a.m.
NEDg Description generation batch_6a2939f004d88190a799790e00f386df completed June 10, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_6a293a8371e08190964a7aac761f8259 completed June 10, 2026, 10:20 a.m.
Created at: April 29, 2026, 9:04 p.m.