Triple

T20208091
Position Surface form Disambiguated ID Type / Status
Subject Port of Surabaya E493411 entity
Predicate servesCity P82 FINISHED
Object Surabaya NE NERFINISHED

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: Surabaya | Statement: [Port of Surabaya, servesCity, Surabaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Surabaya
Context triple: [Port of Surabaya, servesCity, Surabaya]
  • A. Surabaya chosen
    Surabaya is Indonesia’s second-largest city and a key commercial and industrial hub on the island of Java, historically serving as one of the region’s most important seaports.
  • B. Malang
    Malang is a major city in East Java, Indonesia, known for its cool climate, colonial-era architecture, and proximity to popular mountain and volcanic tourist destinations.
  • C. Surakarta
    Surakarta is a historic Javanese city in Central Java, Indonesia, renowned as a traditional cultural center and royal court city closely associated with classical arts such as gamelan music and dance.
  • D. Kediri
    Kediri is a historic city in Indonesia known for its role as a former Javanese kingdom center and as an important economic hub in modern East Java.
  • E. Jember
    Jember is a regency and major urban center in eastern Java, Indonesia, known for its agricultural economy and cultural festivals such as the Jember Fashion Carnaval.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d934f808190bbfeb96f5bf2dfb9 completed April 20, 2026, 6:16 p.m.
Created at: April 11, 2026, 11:38 p.m.