Triple

T8995143
Position Surface form Disambiguated ID Type / Status
Subject Ōita E214883 entity
Predicate hasSisterCity P919 FINISHED
Object Yantai E161767 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: Yantai | Statement: [Ōita, hasSisterCity, Yantai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yantai
Context triple: [Ōita, hasSisterCity, Yantai]
  • A. Yantai chosen
    Yantai is a coastal city in Shandong Province, China, known for its port, wine production, and scenic beaches along the Bohai Sea.
  • B. Dongying
    Dongying is a coastal prefecture-level city in Shandong Province, eastern China, known as the headquarters of the China National Petroleum Corporation and for its location at the mouth of the Yellow River.
  • C. Rizhao
    Rizhao is a coastal city in eastern China known for its sunny climate, beaches, and port on the Yellow Sea.
  • D. Weifang
    Weifang is a prefecture-level city in eastern China known for its kite-making tradition and annual international kite festival.
  • E. Binzhou
    Binzhou is a prefecture-level city in northern Shandong Province, China, located near the lower reaches of the Yellow River and known for its developing industrial and agricultural economy.
  • 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_69ca83a05c608190bdfdbdb25e994b39 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc68ddff288190869731df2c178ff6 completed April 1, 2026, 12:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdb9531748190bd710e0b386b2cbe completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:04 p.m.