Triple

T13687836
Position Surface form Disambiguated ID Type / Status
Subject Catalina E328177 entity
Predicate hasDiminutive P456 FINISHED
Object Cata E740964 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: Cata | Statement: [Catalina, hasDiminutive, Cata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cata
Context triple: [Catalina, hasDiminutive, Cata]
  • A. El Cata chosen
    El Cata is a Dominican singer, songwriter, and producer known for his influential role in modern merengue and Latin urban music, including collaborations with major international artists.
  • B. Cataby
    Cataby is a small locality in Western Australia known primarily as a roadside stop and service point along major transport routes.
  • C. Cateel
    Cateel is a coastal municipality in the province of Davao Oriental in the Philippines, known for its natural attractions such as Aliwagwag Falls.
  • D. Catha
    Catha is an Etruscan solar and possibly lunar goddess associated with light, the heavens, and the transition between day and night.
  • E. 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.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc670968881908e2b4fdf656c7285 completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944981ec8190be5ff39b7c2c70ab completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.