Triple

T4396524
Position Surface form Disambiguated ID Type / Status
Subject 汉阳 E99504 entity
Predicate locatedOnRiver P165 FINISHED
Object 长江 E317825 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: 长江 | Statement: [汉阳, locatedOnRiver, 长江]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 长江
Context triple: [汉阳, locatedOnRiver, 长江]
  • A. 天河
    天河是中国广东省广州市的一个重要市辖区,以其现代化的城市景观和繁华的商业中心而闻名。
  • B. 海河
    海河是中国北方重要的河流和水系之一,流经天津等地并最终注入渤海。
  • C. Yangtze River (Jiang) and Huai River (Huai) chosen
    The Yangtze River (Jiang) and Huai River (Huai) are two major rivers in eastern China that historically formed an important cultural and linguistic boundary region.
  • D. Mao River
    Mao River is a waterway flowing through Shanghai's Qingpu District, contributing to the area's local river network and drainage system.
  • E. Jingjiang River
    Jingjiang River is a historically significant, highly sinuous section of the Yangtze River in central China, known for its sharp bends and extensive river-training works.
  • 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_69b345506b408190b0e3dee616738a7d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b352aca86c8190b5af7e6600072066 completed March 12, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e536e1848190a2517ab351adfe48 completed March 14, 2026, 10:46 p.m.
Created at: March 12, 2026, 11:20 p.m.