Triple

T25525261
Position Surface form Disambiguated ID Type / Status
Subject Qílián Shān E639756 entity
Predicate drainage P1559 FINISHED
Object Datong River
The Datong River is a significant river in northwestern China that drains the Qilian Mountains and serves as an important tributary of the upper Yellow River.
 E1786908 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: Datong River | Statement: [Qílián Shān, drainage, Datong River]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Datong River
Triple: [Qílián Shān, drainage, Datong River]
Generated description
The Datong River is a significant river in northwestern China that drains the Qilian Mountains and serves as an important tributary of the upper Yellow River.

Provenance (5 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_69e75dbf3f9c8190b3f2a75d1b75d127 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f85fabdc8190aa4cab88fd743335 completed May 2, 2026, 1:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e427413881908b70314d1a46f530 completed May 24, 2026, 11:42 a.m.
NEDg Description generation batch_6a12e5c4d7388190b977f2268212f04f completed May 24, 2026, 11:49 a.m.
NED2 Entity disambiguation (via description) batch_6a12e658fe4c8190b4fbbbc2a8a4f796 completed May 24, 2026, 11:51 a.m.
Created at: April 21, 2026, 3:09 p.m.