Triple

T35191276
Position Surface form Disambiguated ID Type / Status
Subject Shudder to Think E1016124 entity
Predicate notableWork P4 FINISHED
Object Funeral at the Movies
Funeral at the Movies is an early 1990s album by the experimental post-hardcore band Shudder to Think, showcasing their off-kilter song structures and distinctive art-rock style.
E2129842 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: Funeral at the Movies | Statement: [Shudder to Think, notableWork, Funeral at the Movies]
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: Funeral at the Movies
Triple: [Shudder to Think, notableWork, Funeral at the Movies]
Generated description
Funeral at the Movies is an early 1990s album by the experimental post-hardcore band Shudder to Think, showcasing their off-kilter song structures and distinctive art-rock style.

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_69f76ddd815c8190b822eea06630f9fb completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78dc734d48190a3fab012eb05dfed completed May 3, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37fb21e680819091689c7ab7cb9a82 completed June 21, 2026, 2:54 p.m.
NEDg Description generation batch_6a37fbbd300c8190bae8823437872acf completed June 21, 2026, 2:57 p.m.
NED2 Entity disambiguation (via description) batch_6a37fc86db2481909015f6fe63315f08 completed June 21, 2026, 3 p.m.
Created at: May 3, 2026, 4:02 p.m.