Triple

T15107137
Position Surface form Disambiguated ID Type / Status
Subject APM Terminals E360816 entity
Predicate parentCompany P254 FINISHED
Object Maersk E455778 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: Maersk | Statement: [APM Terminals, parentCompany, Maersk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maersk
Context triple: [APM Terminals, parentCompany, Maersk]
  • A. A.P. Møller – Mærsk chosen
    A.P. Møller – Mærsk is a Danish multinational conglomerate best known as one of the world’s largest container shipping and logistics companies.
  • B. Mediterranean Shipping Company
    Mediterranean Shipping Company is one of the world’s largest container shipping lines, operating a vast global fleet and network of maritime trade routes.
  • C. Hapag-Lloyd AG
    Hapag-Lloyd AG is a major German international shipping and container transportation company known as one of the world’s leading liner shipping operators.
  • D. Murmansk Shipping Company
    Murmansk Shipping Company is a Russian maritime transport enterprise historically known for operating nuclear-powered icebreakers and supporting Arctic shipping routes.
  • E. DFDS Seaways
    DFDS Seaways is a Danish international shipping and logistics company best known for operating passenger and freight ferry services across Northern Europe.
  • 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_69d85a0491ec8190830960be8fafb994 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0058af8988190977d998f85893836 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69febfe2369881908c7ebbad412d9000 completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3:05 a.m.