Triple

T23739286
Position Surface form Disambiguated ID Type / Status
Subject Rubber Tree Productions E586625 entity
Predicate notableWork P4 FINISHED
Object Maniac
Maniac is a psychological dark comedy-drama miniseries that blends surreal fantasy with character-driven storytelling, best known for its exploration of mental health and experimental drug trials.
E142426 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: Maniac | Statement: [Rubber Tree Productions, notableWork, Maniac]
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: Maniac
Triple: [Rubber Tree Productions, notableWork, Maniac]
Generated description
Maniac is a psychological dark comedy-drama miniseries that blends surreal fantasy with character-driven storytelling, best known for its exploration of mental health and experimental drug trials.

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_69e24908efb08190bf755c3a9b91f222 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bad427f081908eaf96273fec757b completed April 29, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f69689d88819080f0f9ba1ad52b3b completed May 21, 2026, 8:22 p.m.
NEDg Description generation batch_6a0f6a2b96048190b3f1e6465232f4ba completed May 21, 2026, 8:25 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6d4eddf0819081caec7518121664 completed May 21, 2026, 8:38 p.m.
Created at: April 17, 2026, 7:11 p.m.