Triple

T17557553
Position Surface form Disambiguated ID Type / Status
Subject TOML E427624 entity
Predicate usedBy P260 FINISHED
Object Cargo NE NERFINISHED

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: Cargo | Statement: [TOML, usedBy, Cargo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cargo
Context triple: [TOML, usedBy, Cargo]
  • A. Cargo
    Cargo is an Australian post-apocalyptic horror drama film best known for its emotional story of a father trying to save his infant daughter during a zombie outbreak.
  • B. Cargo chosen
    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. Cargo system
    The Cargo system is a traditional Mesoamerican civil-religious hierarchy in which community members rotate through unpaid public and ceremonial offices, reinforcing social cohesion and cultural identity.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889df6dc081908f67dbadc03c07ee completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4562413d08190acaa5272046d3626 completed April 19, 2026, 4:12 a.m.
Created at: April 10, 2026, 5:50 a.m.