Triple

T13696120
Position Surface form Disambiguated ID Type / Status
Subject Weather or Not E328387 entity
Predicate featuresArtist P1952 FINISHED
Object Catero
Catero is a musical artist known for collaborating on the track "Weather or Not."
 E1055131 NE FINISHED

How this triple was built (4 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: Catero | Statement: [Weather or Not, featuresArtist, Catero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Catero
Context triple: [Weather or Not, featuresArtist, Catero]
  • A. Caterinella
    Caterinella is a feminine given name, likely used as an affectionate or diminutive variant of the name Caterina.
  • B. Trino
    Trino is a small historic town in the Piedmont region of northern Italy, known for its agricultural surroundings and proximity to the Po River.
  • C. Trino
    Trino is a high-performance, distributed SQL query engine designed for interactive analytics across large-scale, heterogeneous data sources.
  • D. Catu
    Catu is a municipality in the state of Bahia, Brazil, located within the Metropolitan Region of Salvador and known historically for its role in regional agriculture and oil production.
  • E. Kotěra
    Kotěra is a Czech surname most notably associated with Jan Kotěra, a pioneering architect of modern architecture in Central Europe.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Catero
Triple: [Weather or Not, featuresArtist, Catero]
Generated description
Catero is a musical artist known for collaborating on the track "Weather or Not."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Catero
Target entity description: Catero is a musical artist known for collaborating on the track "Weather or Not."
  • A. Caterinella
    Caterinella is a feminine given name, likely used as an affectionate or diminutive variant of the name Caterina.
  • B. Trino
    Trino is a small historic town in the Piedmont region of northern Italy, known for its agricultural surroundings and proximity to the Po River.
  • C. Trino
    Trino is a high-performance, distributed SQL query engine designed for interactive analytics across large-scale, heterogeneous data sources.
  • D. Catu
    Catu is a municipality in the state of Bahia, Brazil, located within the Metropolitan Region of Salvador and known historically for its role in regional agriculture and oil production.
  • E. Kotěra
    Kotěra is a Czech surname most notably associated with Jan Kotěra, a pioneering architect of modern architecture in Central Europe.
  • F. None of above. chosen

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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8773f388190b2413b1e05fd5fd7 completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79453395481909d651cb3a128f23d completed May 3, 2026, 6:30 p.m.
NEDg Description generation batch_69f79655d5f08190a3cbf3e12e2ffa67 completed May 3, 2026, 6:39 p.m.
NED2 Entity disambiguation (via description) batch_69f7972a1cf48190a1d435227414967a completed May 3, 2026, 6:42 p.m.
Created at: April 9, 2026, 9:54 p.m.