Triple

T28589857
Position Surface form Disambiguated ID Type / Status
Subject Shangjing E723611 entity
Predicate locatedOn P40 FINISHED
Object Xilamulun River
The Xilamulun River is a river in northeastern China that flows through Inner Mongolia and historically supported important Khitan settlements such as the Liao dynasty capital Shangjing.
 E2293820 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: Xilamulun River | Statement: [Shangjing, locatedOn, Xilamulun 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: Xilamulun River
Triple: [Shangjing, locatedOn, Xilamulun River]
Generated description
The Xilamulun River is a river in northeastern China that flows through Inner Mongolia and historically supported important Khitan settlements such as the Liao dynasty capital Shangjing.

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_69f01d7f92e481909847f5f3f3174a89 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f651b2a2388190b269d7b5e931794a completed May 2, 2026, 7:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7b09be4b6c81908fe478d36749588b completed Aug. 11, 2026, 11:38 a.m.
NEDg Description generation batch_6a7b0c3918f8819098de98dd1768d394 completed Aug. 11, 2026, 11:49 a.m.
NED2 Entity disambiguation (via description) batch_6a7b0dad120c8190a833dbdee538449d completed Aug. 11, 2026, 11:55 a.m.
Created at: April 28, 2026, 4:19 a.m.