Triple

T23584080
Position Surface form Disambiguated ID Type / Status
Subject Halloween: Resurrection E582286 entity
Predicate character P662 FINISHED
Object Freddie Harris
Freddie Harris is a character in the Halloween horror film series, portrayed as a reality show producer whose online broadcast from Michael Myers' childhood home goes disastrously wrong.
E1622920 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: Freddie Harris | Statement: [Halloween: Resurrection, character, Freddie Harris]
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: Freddie Harris
Triple: [Halloween: Resurrection, character, Freddie Harris]
Generated description
Freddie Harris is a character in the Halloween horror film series, portrayed as a reality show producer whose online broadcast from Michael Myers' childhood home goes disastrously wrong.

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_69e248f8d8248190acd5aee77f0d1709 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b02f68288190b348c7558a6a24e1 completed April 29, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0face7db9881909590d4ac075484a1 completed May 22, 2026, 1:10 a.m.
NEDg Description generation batch_6a0fadd36d448190a96b5b9be36141bf completed May 22, 2026, 1:13 a.m.
NED2 Entity disambiguation (via description) batch_6a0fae34bb948190b8f936d8f47d7c41 completed May 22, 2026, 1:15 a.m.
Created at: April 17, 2026, 6:40 p.m.