Triple

T24079200
Position Surface form Disambiguated ID Type / Status
Subject Skinny Puppy E596458 entity
Predicate notableWork P4 FINISHED
Object Too Dark Park
Too Dark Park is a 1990 industrial music album by Skinny Puppy, noted for its dense, abrasive soundscapes and dark, experimental themes.
 E1616203 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: Too Dark Park | Statement: [Skinny Puppy, notableWork, Too Dark Park]
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: Too Dark Park
Triple: [Skinny Puppy, notableWork, Too Dark Park]
Generated description
Too Dark Park is a 1990 industrial music album by Skinny Puppy, noted for its dense, abrasive soundscapes and dark, experimental themes.

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_69e288c3999c8190809b282a04813dec completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1db20ca648190bb168808623119da completed April 29, 2026, 10:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f966eda448190adc2845a9a11aaf1 completed May 21, 2026, 11:34 p.m.
NEDg Description generation batch_6a0f971a0f108190ba6d5b57da2acbdf completed May 21, 2026, 11:36 p.m.
NED2 Entity disambiguation (via description) batch_6a0f9817d9248190aa2f7cc8fc2916bf completed May 21, 2026, 11:41 p.m.
Created at: April 17, 2026, 10:43 p.m.