Triple

T9816062
Position Surface form Disambiguated ID Type / Status
Subject Nerima, Tokyo E238406 entity
Predicate hasSisterCity P919 FINISHED
Object Haikou, Hainan E197372 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: Haikou, Hainan | Statement: [Nerima, Tokyo, hasSisterCity, Haikou, Hainan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haikou, Hainan
Context triple: [Nerima, Tokyo, hasSisterCity, Haikou, Hainan]
  • A. Haikou chosen
    Haikou is the capital and largest city of China’s Hainan Province, known as a key port, commercial hub, and tropical coastal destination.
  • B. Sanya
    Sanya is a major resort city on the southern coast of China’s Hainan Island, known for its tropical climate and popular beach tourism.
  • C. Wanning
    Wanning is a county-level coastal city in southeastern Hainan, China, known for its tropical climate, beaches, and surf-friendly bays.
  • D. Wenchang
    Wenchang is a coastal city in northeastern Hainan, China, known as a cultural center and important homeland of many overseas Chinese.
  • E. Boao
    Boao is a coastal town in Hainan, China, best known for hosting the annual Boao Forum for Asia, a major international economic and political conference.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f341648190bf8343e1124085cb completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6525a4af08190bcd8455e95a2f3ae completed April 8, 2026, 1:04 p.m.
Created at: March 30, 2026, 8:30 p.m.