Triple

T9249893
Position Surface form Disambiguated ID Type / Status
Subject macOS Catalina E222295 entity
Predicate codename P2980 FINISHED
Object Catalina E328177 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: Catalina | Statement: [macOS Catalina, codename, Catalina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catalina
Context triple: [macOS Catalina, codename, Catalina]
  • A. Catalina chosen
    Catalina is a feminine given name used in various Romance-language cultures, often considered a form of Catherine.
  • B. Santa Elena
    Santa Elena was a 16th-century Spanish colonial settlement on present-day Parris Island, South Carolina, that served as the capital of Spanish Florida for a time.
  • C. Santa Elena
    Santa Elena is a small town in western Belize, located near San Ignacio and serving as a local commercial and residential hub in the Cayo District.
  • D. Catalinas
    Catalinas is a station on the Buenos Aires Underground, located in the central business district near the Catalinas Norte office complex.
  • E. Helene (Santa Elena)
    Helene (Santa Elena) is a small, sparsely populated Caribbean island off the eastern end of Roatán in Honduras, known for its remote beaches, traditional communities, and rich marine life.
  • 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_69ca841d2b18819089f9faf5b2c2aec0 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd05f7e9848190939f9199d0c1a572 completed April 1, 2026, 11:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d077fed7888190a5d36bc2ee4c2bd2 completed April 4, 2026, 2:31 a.m.
Created at: March 30, 2026, 7:31 p.m.