Triple

T6924538
Position Surface form Disambiguated ID Type / Status
Subject Liao River E160271 entity
Predicate associatedCity P3207 FINISHED
Object Panjin E377000 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: Panjin | Statement: [Liao River, associatedCity, Panjin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Panjin
Context triple: [Liao River, associatedCity, Panjin]
  • A. Panjin chosen
    Panjin is an industrial and oil-producing city in northeastern China, best known for its striking Red Beach wetlands along the Bohai Sea.
  • B. Yingkou
    Yingkou is a coastal port city in northeastern China’s Liaoning Province, known as an important industrial and shipping hub 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. Lianyungang
    Lianyungang is a major coastal city and seaport in eastern China, serving as an important transportation and trade hub on the Yellow Sea.
  • E. 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.
  • 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_69c6884d350081908d8a970e4d40ad78 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9fea8d08190b6099a24fbac7de5 completed March 27, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75859735081909382f1542271a1e4 completed March 28, 2026, 4:26 a.m.
Created at: March 27, 2026, 2:26 p.m.