Triple

T31340266
Position Surface form Disambiguated ID Type / Status
Subject Hobo with a Shotgun E799286 entity
Predicate starring P1507 FINISHED
Object Brian Downey
Brian Downey is a Canadian actor best known for his roles in cult and genre films and television, including the science fiction series "Lexx" and the exploitation film "Hobo with a Shotgun."
E1959767 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: Brian Downey | Statement: [Hobo with a Shotgun, starring, Brian Downey]
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: Brian Downey
Triple: [Hobo with a Shotgun, starring, Brian Downey]
Generated description
Brian Downey is a Canadian actor best known for his roles in cult and genre films and television, including the science fiction series "Lexx" and the exploitation film "Hobo with a Shotgun."

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_69f224e3f6ac8190a13488516abca7c9 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69f1340a48190be75fd54fa524d3e completed May 3, 2026, 1:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2ad22c465481908e7fc6a7b67c5b41 completed June 11, 2026, 3:20 p.m.
NEDg Description generation batch_6a2ad3acc9d08190ad9aa7192a812992 completed June 11, 2026, 3:26 p.m.
NED2 Entity disambiguation (via description) batch_6a2ad4776f9481908b0216064edce759 completed June 11, 2026, 3:29 p.m.
Created at: April 29, 2026, 9:16 p.m.