Triple

T23523706
Position Surface form Disambiguated ID Type / Status
Subject Dunajec River basin E574575 entity
Predicate hasTributary P415 FINISHED
Object Dłubnia River
The Dłubnia River is a river in southern Poland that flows through the Kraków area before joining the Vistula.
E1615963 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: Dłubnia River | Statement: [Dunajec River basin, hasTributary, Dłubnia 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: Dłubnia River
Triple: [Dunajec River basin, hasTributary, Dłubnia River]
Generated description
The Dłubnia River is a river in southern Poland that flows through the Kraków area before joining the Vistula.

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_69e245bb3dcc8190ba9a2b35972b58d0 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1ac71ec8881909bfb706efdc2518f completed April 29, 2026, 7 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f961f79bc81909da33922b038452f completed May 21, 2026, 11:32 p.m.
NEDg Description generation batch_6a0f974fb2e08190a535a92ead622159 completed May 21, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_6a0f9817d9248190aa2f7cc8fc2916bf completed May 21, 2026, 11:41 p.m.
Created at: April 17, 2026, 6:09 p.m.