Triple

T38035662
Position Surface form Disambiguated ID Type / Status
Subject Lake Nero E949344 entity
Predicate inflow P415 FINISHED
Object Kurost River
Kurost River is a watercourse in Russia that serves as one of the main tributaries feeding Lake Nero near the historic town of Rostov.
E2291912 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: Kurost River | Statement: [Lake Nero, inflow, Kurost 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: Kurost River
Triple: [Lake Nero, inflow, Kurost River]
Generated description
Kurost River is a watercourse in Russia that serves as one of the main tributaries feeding Lake Nero near the historic town of Rostov.

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_69f76eff0bb0819084bc4e63997bd039 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc99e541c8190af421d3342b81918 completed May 6, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5ca3876b4081909a190ea013718671 completed July 19, 2026, 10:14 a.m.
NEDg Description generation batch_6a5ca3e3e25c81909c77eca54e14d821 completed July 19, 2026, 10:16 a.m.
NED2 Entity disambiguation (via description) batch_6a5ca43af4f88190bf85f871951d993d completed July 19, 2026, 10:17 a.m.
Created at: May 3, 2026, 4:20 p.m.