Triple

T19872425
Position Surface form Disambiguated ID Type / Status
Subject 洛河 E477550 entity
Predicate 别名 P39 FINISHED
Object 洛水 — NE NERFINISHED

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: 洛水 | Statement: [洛河, 别名, 洛水]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 洛水
Context triple: [洛河, 别名, 洛水]
  • A. 洛河 chosen
    洛河是一条位于中国中部、历史文化底蕴深厚的河流，在中华古代神话与文学中具有重要地位。
  • B. 延河
    延河是中国黄土高原上一条重要支流河流，流经陕西省延安地区并最终汇入黄河。
  • C. 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。
  • D. 滹沱河
    滹沱河是中国华北地区一条重要河流，流经山西和河北等地并最终汇入海河水系。
  • E. 汉江
    汉江是中国长江中游最大的支流之一，流经陕西、湖北等地并在武汉与长江汇合。
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e658d826f88190be04188997952d1b completed April 20, 2026, 4:48 p.m.
Created at: April 10, 2026, 1:51 p.m.