Triple

T5051486
Position Surface form Disambiguated ID Type / Status
Subject Asia-Pacific ports E113794 entity
Predicate hasPart P35 FINISHED
Object Port of Jakarta E23519 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: Port of Jakarta | Statement: [Asia-Pacific ports, hasPart, Port of Jakarta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Port of Jakarta
Context triple: [Asia-Pacific ports, hasPart, Port of Jakarta]
  • A. Tanjung Priok chosen
    Tanjung Priok is Indonesia’s busiest and largest seaport, serving as the main maritime gateway to Jakarta and the island of Java.
  • B. Port of Cirebon
    The Port of Cirebon is a commercial seaport on the north coast of West Java, Indonesia, serving regional trade and transportation for the city of Cirebon and its surrounding areas.
  • C. Port of Trisakti
    The Port of Trisakti is a major seaport and key commercial gateway serving the city of Banjarmasin and the surrounding region in South Kalimantan, Indonesia.
  • D. Sunda Kelapa
    Sunda Kelapa is the historic old port area of Jakarta, Indonesia, known as a key trading hub in the region since precolonial times.
  • E. Soekarno-Hatta Port
    Soekarno-Hatta Port is a major seaport in Makassar, Indonesia, serving as an important hub for maritime trade and passenger transport in eastern Indonesia.
  • 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_69bd443aa1f88190abb992d138f2cf42 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7426fc8081908a8227f73168c235 completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb0fd25c081909ddf2d8eb77f33e7 completed March 21, 2026, 2:53 p.m.
Created at: March 20, 2026, 1:37 p.m.