Triple

T32173255
Position Surface form Disambiguated ID Type / Status
Subject Maniac Cop E821766 entity
Predicate mainCharacter P1183 FINISHED
Object Matt Cordell
Matt Cordell is the vengeful, undead police officer who serves as the central antagonist in the Maniac Cop horror film series.
E2056427 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: Matt Cordell | Statement: [Maniac Cop, mainCharacter, Matt Cordell]
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: Matt Cordell
Triple: [Maniac Cop, mainCharacter, Matt Cordell]
Generated description
Matt Cordell is the vengeful, undead police officer who serves as the central antagonist in the Maniac Cop horror film series.

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_69f3490699a48190bbef96b198e8fade completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6ba77b7288190a0f2b12c5df8ee3e completed May 3, 2026, 3:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35a64d15d481909dc07dc58c48e5e5 completed June 19, 2026, 8:27 p.m.
NEDg Description generation batch_6a35a76b3d788190b7b67f323b0ed7f4 completed June 19, 2026, 8:32 p.m.
NED2 Entity disambiguation (via description) batch_6a35a7f69078819083fcc1f883baf788 completed June 19, 2026, 8:35 p.m.
Created at: May 1, 2026, 12:33 a.m.