Triple

T14011098
Position Surface form Disambiguated ID Type / Status
Subject Lüshunkou District E337079 entity
Predicate hasHistoricalName P2834 FINISHED
Object Ryojun E926912 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: Ryojun | Statement: [Lüshunkou District, hasHistoricalName, Ryojun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ryojun
Context triple: [Lüshunkou District, hasHistoricalName, Ryojun]
  • A. Ryojun chosen
    Ryojun is the former Japanese name for Lüshunkou, a strategically important port city in northeastern China historically known for its military significance.
  • B. Ryūō
    Ryūō is a town in Shiga Prefecture, Japan, known for its location near Lake Biwa and its blend of rural landscapes with growing commercial development.
  • C. Kenjirō
    Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
  • D. Yorihito
    Yorihito was a Japanese imperial prince of the Higashifushimi-no-miya house who served as a high-ranking naval officer during the late Meiji and Taishō periods.
  • E. Shinpei
    Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, and entertainment.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed5cfd0819085b9c860b119a9de completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd1bb1c48190b5d2b4167c756abf completed May 9, 2026, 7:07 a.m.
Created at: April 9, 2026, 10:19 p.m.