Triple

T12725494
Position Surface form Disambiguated ID Type / Status
Subject Tema E304094 entity
Predicate hasPort P35 FINISHED
Object Tema Harbour E182928 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: Tema Harbour | Statement: [Tema, hasPort, Tema Harbour]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tema Harbour
Context triple: [Tema, hasPort, Tema Harbour]
  • A. Tema Harbour chosen
    Tema Harbour is a major seaport and industrial hub on Ghana’s Atlantic coast, serving as one of the country’s primary gateways for international maritime trade.
  • B. Harborland
    Harborland is a popular waterfront shopping and entertainment district in Kobe, Japan, known for its modern malls, restaurants, and scenic harbor views.
  • C. The Harbour
    The Harbour is a creative work by Croatian illustrator, animator, and filmmaker Milan Trenc, known for his distinctive, surreal visual style.
  • D. HarbourFront
    HarbourFront is a major waterfront district and transport hub in southern Singapore, known for its cruise centre, shopping malls, and gateway access to Sentosa Island.
  • E. Harbourside
    Harbourside is a residential neighborhood in the city of Irvine, California, known for its planned suburban layout and proximity to local amenities.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96415ebe48190ae935bc3a9b00f65 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c85c6b88190bbdd94a43915a7a4 completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:25 p.m.