Triple

T30133433
Position Surface form Disambiguated ID Type / Status
Subject Liaocheng E765913 entity
Predicate hasRiver P165 FINISHED
Object Majia River
The Majia River is a significant river in northern China that flows through Shandong Province, including the city of Liaocheng, and ultimately drains toward the Bohai Sea.
 E2295062 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: Majia River | Statement: [Liaocheng, hasRiver, Majia 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: Majia River
Triple: [Liaocheng, hasRiver, Majia River]
Generated description
The Majia River is a significant river in northern China that flows through Shandong Province, including the city of Liaocheng, and ultimately drains toward the Bohai Sea.

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_69f22477d1a081908df2b7e6ed16859d completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67e4a4b5c8190b5bc97169f9153de completed May 2, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7cfc19ecc8819087e93f66240a41a4 completed Aug. 12, 2026, 11:04 p.m.
NEDg Description generation batch_6a7cfd1e0628819097369112b2377041 completed Aug. 12, 2026, 11:09 p.m.
NED2 Entity disambiguation (via description) batch_6a7cfd7373d8819089377604ee2898a0 completed Aug. 12, 2026, 11:10 p.m.
Created at: April 29, 2026, 7:15 p.m.