Triple

T16058415
Position Surface form Disambiguated ID Type / Status
Subject MAB Kargo E389541 entity
Predicate hasAbbreviation P43 FINISHED
Object MAB Kargo E389541 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: MAB Kargo | Statement: [MAB Kargo, hasAbbreviation, MAB Kargo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MAB Kargo
Context triple: [MAB Kargo, hasAbbreviation, MAB Kargo]
  • A. MAB Kargo chosen
    MAB Kargo is the cargo and logistics arm of Malaysia’s national aviation group, providing air freight and related services across regional and international markets.
  • B. YTO Cargo Airlines
    YTO Cargo Airlines is a Chinese cargo airline that operates domestic and international freight services as part of the YTO Express logistics network.
  • C. TNT Express
    TNT Express is an international courier and logistics company known for its global parcel delivery and express mail services.
  • D. KAI Logistik
    KAI Logistik is a logistics and freight services company operating under Indonesia’s state-owned railway operator Kereta Api Indonesia.
  • E. Maximus Air Cargo
    Maximus Air Cargo is a UAE-based cargo airline specializing in outsized and heavy-lift air freight operations.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837634248190a99cc454ad1e99e0 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbe678fc8190b36737a9cd29691c completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:57 a.m.