Triple

T9894076
Position Surface form Disambiguated ID Type / Status
Subject Toba E181524 entity
Predicate hasPort P35 FINISHED
Object Toba Port E181524 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: Toba Port | Statement: [Toba, hasPort, Toba Port]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toba Port
Context triple: [Toba, hasPort, Toba Port]
  • A. Toba chosen
    Toba is a coastal city in central Japan’s Mie Prefecture, known for its pearl cultivation, scenic bays, and maritime heritage.
  • B. Toba Batak
    Toba Batak is an Austronesian language spoken primarily by the Toba Batak people of North Sumatra, Indonesia.
  • C. Telaga Harbour
    Telaga Harbour is a marina and port on Langkawi Island in Malaysia, known as a gateway for yachts and ferries and as a hub for tourism and waterfront leisure activities.
  • D. Palu Bay
    Palu Bay is a coastal inlet on the island of Sulawesi in Indonesia, known for its narrow, elongated shape and vulnerability to tsunamis and seismic activity.
  • E. Lumban
    Lumban is a municipality in the Philippine province of Laguna known for its traditional hand-embroidered textiles and scenic lakeside setting along Laguna de Bay.
  • 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_69ca8283a6708190801af7a25a7ebb9f completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb48271d48190b718c7f6b2fe315b completed April 2, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20d888b408190a68ff55d63558478 completed April 5, 2026, 7:21 a.m.
Created at: March 30, 2026, 8:39 p.m.