Triple

T9919071
Position Surface form Disambiguated ID Type / Status
Subject Tulsa E185942 entity
Predicate hasSisterCity P919 FINISHED
Object Kaohsiung E151217 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: Kaohsiung | Statement: [Tulsa, hasSisterCity, Kaohsiung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaohsiung
Context triple: [Tulsa, hasSisterCity, Kaohsiung]
  • A. Kaohsiung chosen
    Kaohsiung is a major port city in southern Taiwan known for its heavy industry, modern harborfront, and growing cultural and arts scene.
  • B. Tainan
    Tainan is a historic city in southern Taiwan known for its well-preserved temples, traditional culture, and status as the island’s former capital.
  • C. Keelung
    Keelung is a major port city in northeastern Taiwan known for its busy harbor, seafood markets, and coastal scenery.
  • D. Pingtung City
    Pingtung City is an urban center in southern Taiwan known as the political and economic hub of Pingtung County.
  • E. Taichung
    Taichung is a major city in central Taiwan known for its cultural attractions, mild climate, and role as an important economic and transportation hub.
  • 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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb5685a908190ab3e55b9bf9613f6 completed April 2, 2026, 12:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20df77f208190b550b888bf7b55ea completed April 5, 2026, 7:23 a.m.
Created at: March 30, 2026, 8:42 p.m.