Triple

T10797549
Position Surface form Disambiguated ID Type / Status
Subject Burchardkai container terminal E254749 entity
Predicate operator P179 FINISHED
Object HHLA E883954 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: HHLA | Statement: [Burchardkai container terminal, operator, HHLA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HHLA
Context triple: [Burchardkai container terminal, operator, HHLA]
  • A. HHLA chosen
    HHLA is a major German logistics and port operating company best known for managing key container terminals in the Port of Hamburg.
  • B. Hamburg Port Authority
    The Hamburg Port Authority is the public institution responsible for managing, developing, and regulating the Port of Hamburg’s infrastructure and maritime operations.
  • C. Hamburger Hafen und Logistik AG
    Hamburger Hafen und Logistik AG is a major German port and logistics company that operates key container terminals in the Port of Hamburg and provides integrated transport and logistics services.
  • D. HafenCity Hamburg GmbH
    HafenCity Hamburg GmbH is the municipal development company responsible for planning and realizing Hamburg’s large-scale HafenCity urban waterfront redevelopment project.
  • E. S7 Cargo
    S7 Cargo is the air freight and logistics division of Russia’s S7 Group, providing cargo transportation services on the airline’s route network.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73333dc4081909faa40c10bce2735 completed April 9, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69de566352608190ab15e3a4b690c9a5 completed April 14, 2026, 2:59 p.m.
Created at: April 8, 2026, 9:17 p.m.