Triple

T24985841
Position Surface form Disambiguated ID Type / Status
Subject House of Wax (2005 film) E625303 entity
Predicate mainCharacter P1183 FINISHED
Object Carly Jones
Carly Jones is the resourceful and determined protagonist of the 2005 horror film "House of Wax," who fights to survive a deadly encounter in a sinister wax museum.
E1669620 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: Carly Jones | Statement: [House of Wax (2005 film), mainCharacter, Carly Jones]
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: Carly Jones
Triple: [House of Wax (2005 film), mainCharacter, Carly Jones]
Generated description
Carly Jones is the resourceful and determined protagonist of the 2005 horror film "House of Wax," who fights to survive a deadly encounter in a sinister wax museum.

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_69e2ff254570819093d197b1900305ac completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f4490a4a508190bdd6c2dde03e251a completed May 1, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067ae505881909e88eca304e74c2e completed May 22, 2026, 2:26 p.m.
NEDg Description generation batch_6a106844f694819082bb12621dcb700b completed May 22, 2026, 2:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1068b5f1048190a4ff23ddfd76abd6 completed May 22, 2026, 2:31 p.m.
Created at: April 18, 2026, 6:03 a.m.