Triple

T8527153
Position Surface form Disambiguated ID Type / Status
Subject North Jakarta E201845 entity
Predicate contains P35 FINISHED
Object Tanjung Priok 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: Tanjung Priok | Statement: [North Jakarta, contains, Tanjung Priok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanjung Priok
Context triple: [North Jakarta, contains, Tanjung Priok]
  • 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 Banten
    The Port of Banten was a major Southeast Asian trading harbor that served as a key commercial hub for the Sultanate of Banten, connecting regional and international maritime trade routes.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6477100819081fa20cb6b8ea3d7 completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d49c1408190b7c23739409d1e3d completed April 2, 2026, 1:21 p.m.
Created at: March 30, 2026, 6:16 p.m.