Triple

T14171037
Position Surface form Disambiguated ID Type / Status
Subject Maverick Records E351206 entity
Predicate signedArtist P16560 FINISHED
Object Filter E596441 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: Filter | Statement: [Maverick Records, signedArtist, Filter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Filter
Context triple: [Maverick Records, signedArtist, Filter]
  • A. Filter chosen
    Filter is an American industrial rock band formed by former Nine Inch Nails touring guitarist Richard Patrick, known for hits like "Hey Man Nice Shot" and "Take a Picture."
  • B. Filter House
    Filter House is a critically acclaimed short story collection by American speculative fiction author Shawl Nisi, noted for its inventive, genre-blending narratives.
  • C. Filter Encoding
    Filter Encoding is an Open Geospatial Consortium (OGC) standard XML-based language for expressing queries and filters on geospatial and attribute data in web services.
  • D. Filtvet
    Filtvet is a small village in the former municipality of Hurum in Viken county, Norway, known for its coastal location along the Oslofjord.
  • E. Digital Filters
    "Digital Filters" is a foundational work in signal processing that systematically presents the theory, design, and practical implementation of filters for processing discrete-time signals.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b5dcbc8190b0cfcce5e6c6d582 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf808e6088190a607903be0f2adc7 completed May 7, 2026, 8:37 p.m.
Created at: April 10, 2026, 1:01 a.m.