Triple

T31096993
Position Surface form Disambiguated ID Type / Status
Subject Beyond Borders E792558 entity
Predicate writer P1360 FINISHED
Object Caspian Tredwell-Owen
Caspian Tredwell-Owen is a British screenwriter best known for his work on feature films in the early 2000s.
E1141865 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: Caspian Tredwell-Owen | Statement: [Beyond Borders, writer, Caspian Tredwell-Owen]
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: Caspian Tredwell-Owen
Triple: [Beyond Borders, writer, Caspian Tredwell-Owen]
Generated description
Caspian Tredwell-Owen is a British screenwriter best known for his work on feature films in the early 2000s.

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_69f224cf157c81909e2d2bd88c9282c3 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6966f0fa08190867c7715ba80b0b3 completed May 3, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b36171881909d90235b4b9bc633 completed June 10, 2026, 9:15 a.m.
NEDg Description generation batch_6a292c16ae008190bac905923bd17425 completed June 10, 2026, 9:19 a.m.
NED2 Entity disambiguation (via description) batch_6a292caa0590819087d6b9d576701697 completed June 10, 2026, 9:21 a.m.
Created at: April 29, 2026, 9:03 p.m.