Triple

T7918771
Position Surface form Disambiguated ID Type / Status
Subject Zarya E183891 entity
Predicate alsoKnownAs P39 FINISHED
Object Functional Cargo Block E183892 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: Functional Cargo Block | Statement: [Zarya, alsoKnownAs, Functional Cargo Block]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Functional Cargo Block
Context triple: [Zarya, alsoKnownAs, Functional Cargo Block]
  • A. Functional Cargo Block chosen
    The Functional Cargo Block (FGB), also known as Zarya, is the first module of the International Space Station, providing initial power, propulsion, and storage capabilities.
  • B. Cargo
    Cargo is Rust’s official build and dependency management tool that streamlines compiling code, managing libraries, and distributing Rust packages.
  • C. Cargo
    Cargo is a small rural town in the Central West region of New South Wales, Australia, known for its agricultural surroundings and village community.
  • D. LOT Cargo
    LOT Cargo is the air freight and cargo handling division of LOT Polish Airlines, providing logistics and cargo transport services on the carrier’s route network.
  • E. CargoNet
    CargoNet is a major Norwegian rail freight company that transports goods across Norway and into neighboring countries using the national railway network.
  • 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_69ca828efbe48190bd48482650182e79 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a8fbbb48190b50def4941761a31 completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5beea7988190972f7d02881d98f6 completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:05 p.m.