Triple

T8716264
Position Surface form Disambiguated ID Type / Status
Subject Panamax E206900 entity
Predicate followedBy P78 FINISHED
Object New Panamax E41164 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: New Panamax | Statement: [Panamax, followedBy, New Panamax]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: New Panamax
Context triple: [Panamax, followedBy, New Panamax]
  • A. Neopanamax chosen
    Neopanamax is a class of large cargo ships specifically designed to fit the expanded locks of the Panama Canal, allowing greater capacity than the earlier Panamax standard.
  • B. Panamax
    Panamax is the maximum size limit for ships that can transit the original locks of the Panama Canal, defining a key standard in global maritime shipping.
  • C. Gulftainer
    Gulftainer is a global port management and logistics company based in the United Arab Emirates, known for operating and developing container terminals and cargo facilities worldwide.
  • D. Panama Limited
    Panama Limited was a famed luxury overnight passenger train that operated between Chicago and New Orleans on the Illinois Central Railroad.
  • E. Mærsk Mc-Kinney Møller
    Mærsk Mc-Kinney Møller was a prominent Danish shipping magnate and philanthropist, best known for leading the A.P. Moller–Maersk Group and funding major cultural projects in Denmark.
  • 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_69ca83572d4881909bef3be2b578d539 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5cd9c2a08190a65ab0ce573153d2 completed March 31, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28df657881908c1fc67c2c777cea completed April 3, 2026, 2:41 a.m.
Created at: March 30, 2026, 6:35 p.m.