Triple

T31176817
Position Surface form Disambiguated ID Type / Status
Subject Lake Viljandi E794771 entity
Predicate outflow P967 FINISHED
Object Raudna River
The Raudna River is a watercourse in southern Estonia that drains Lake Viljandi and flows through Viljandi County’s rural landscape.
 E2295373 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: Raudna River | Statement: [Lake Viljandi, outflow, Raudna 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: Raudna River
Triple: [Lake Viljandi, outflow, Raudna River]
Generated description
The Raudna River is a watercourse in southern Estonia that drains Lake Viljandi and flows through Viljandi County’s rural landscape.

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_69f224d5b9708190b6ca79ad2fd3a28a completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f698b5c3588190bafb7f260d51de35 completed May 3, 2026, 12:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7d47c0cb308190ae987ce9bbc1069a completed Aug. 13, 2026, 4:27 a.m.
NEDg Description generation batch_6a7d488bc92c8190b7b114c2c4c205d8 completed Aug. 13, 2026, 4:31 a.m.
NED2 Entity disambiguation (via description) batch_6a7d48dae1908190a466dcb9b22c0d42 completed Aug. 13, 2026, 4:32 a.m.
Created at: April 29, 2026, 9:08 p.m.