Triple

T26766944
Position Surface form Disambiguated ID Type / Status
Subject Wilmington Air Park E674963 entity
Predicate hasCargoFocus P180127 FINISHED
Object yes LITERAL 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: yes | Statement: [Wilmington Air Park, hasCargoFocus, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCargoFocus
Context triple: [Wilmington Air Park, hasCargoFocus, yes]
  • A. hasCargoRole
    Indicates that an entity participates in a cargo-related capacity or function within a transport, shipment, or logistics context.
  • B. hasCargoHold
    Indicates that something possesses a dedicated space or compartment for storing or transporting cargo.
  • C. hasCargoDivision
    Indicates that an organization possesses a specific division or unit responsible for cargo-related operations or services.
  • D. hasCargoHandlingMode
    Indicates the method or procedure by which cargo is handled, loaded, or unloaded in a given context.
  • E. hasCargoServices
    Indicates that an entity provides or is equipped to handle cargo transportation or freight services for another entity or location.
  • F. None of above. chosen

Provenance (4 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_69eecda85298819097ee1c38a3d772e7 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f73223675481908c1bc3208c0f5284 completed May 3, 2026, 11:31 a.m.
PD Predicate disambiguation batch_69f7317690108190b3aae2cd2e1d069e completed May 3, 2026, 11:28 a.m.
PDg Predicate description generation batch_69f73221eef88190bd8905e6e9f5a586 completed May 3, 2026, 11:31 a.m.
Created at: April 27, 2026, 4 a.m.