Triple

T33727475
Position Surface form Disambiguated ID Type / Status
Subject The Great Danton E864182 entity
Predicate spouse P13 FINISHED
Object Julia McCullough
Julia McCullough is a character in the film "The Prestige," known as the wife of magician Alfred Borden (performing under the name The Great Danton) whose tragic fate deeply impacts the story's central rivalry.
E324283 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: Julia McCullough | Statement: [The Great Danton, spouse, Julia McCullough]
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: Julia McCullough
Triple: [The Great Danton, spouse, Julia McCullough]
Generated description
Julia McCullough is a character in the film "The Prestige," known as the wife of magician Alfred Borden (performing under the name The Great Danton) whose tragic fate deeply impacts the story's central rivalry.

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_69f3498a64cc8190b4b414c67b280d93 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fb1b91bc8190a40733039fe939b3 completed May 3, 2026, 7:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36a01356b4819081fddc140a7d1359 completed June 20, 2026, 2:13 p.m.
NEDg Description generation batch_6a36a10516cc8190b65487ff244ebd92 completed June 20, 2026, 2:17 p.m.
NED2 Entity disambiguation (via description) batch_6a36a1b1393481908afcb734e6eacb53 completed June 20, 2026, 2:20 p.m.
Created at: May 1, 2026, 1:44 a.m.