Triple

T30088739
Position Surface form Disambiguated ID Type / Status
Subject Nuorilang Waterfall E764669 entity
Predicate partOf P40 FINISHED
Object upper Jiuzhaigou scenic route
The upper Jiuzhaigou scenic route is a popular section of China’s Jiuzhaigou Valley National Park known for its high-altitude lakes, waterfalls, and colorful alpine landscapes.
E1898594 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: upper Jiuzhaigou scenic route | Statement: [Nuorilang Waterfall, partOf, upper Jiuzhaigou scenic route]
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: upper Jiuzhaigou scenic route
Triple: [Nuorilang Waterfall, partOf, upper Jiuzhaigou scenic route]
Generated description
The upper Jiuzhaigou scenic route is a popular section of China’s Jiuzhaigou Valley National Park known for its high-altitude lakes, waterfalls, and colorful alpine landscapes.

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_69f22473c0fc8190a926a8051b3b378b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67d6e9e188190808014372fc2cbd0 completed May 2, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274326796881908b88f934483ff638 completed June 8, 2026, 10:33 p.m.
NEDg Description generation batch_6a2743e893708190a11e3888456906bb completed June 8, 2026, 10:36 p.m.
NED2 Entity disambiguation (via description) batch_6a274507fa3c819098819c5b1c2c4133 completed June 8, 2026, 10:41 p.m.
Created at: April 29, 2026, 7:05 p.m.