Triple

T3408099
Position Surface form Disambiguated ID Type / Status
Subject Liaoning E71823 entity
Predicate majorCity P316 FINISHED
Object Yingkou E303634 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: Yingkou | Statement: [Liaoning, majorCity, Yingkou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yingkou
Context triple: [Liaoning, majorCity, Yingkou]
  • A. Yingkou chosen
    Yingkou is a coastal port city in northeastern China’s Liaoning Province, known as an important industrial and shipping hub on the Bohai Sea.
  • B. Jinzhou
    Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
  • C. Dandong
    Dandong is a northeastern Chinese border city on the Yalu River, known as a key gateway for trade and transport between China and North Korea.
  • D. Dalian
    Dalian is a major port city in northeastern China known for its strategic location on the Liaodong Peninsula, maritime trade, and modern urban development.
  • E. Anshan
    Anshan was an ancient city and region in southwestern Iran that served as an early center of Elamite and later Achaemenid Persian power.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9056acc8190a9c50ec374851ac8 completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b402c6e5bc819099a5148ad509b22d completed March 13, 2026, 12:27 p.m.
Created at: March 8, 2026, 3:15 p.m.