Triple

T17614630
Position Surface form Disambiguated ID Type / Status
Subject Ratmanov Island E429050 entity
Predicate namedAfter P63 FINISHED
Object Dmitry Ratmanov
Dmitry Ratmanov was a Russian naval officer and explorer after whom Ratmanov Island in the Bering Strait is named.
E2028636 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: Dmitry Ratmanov | Statement: [Ratmanov Island, namedAfter, Dmitry Ratmanov]
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: Dmitry Ratmanov
Triple: [Ratmanov Island, namedAfter, Dmitry Ratmanov]
Generated description
Dmitry Ratmanov was a Russian naval officer and explorer after whom Ratmanov Island in the Bering Strait is named.

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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d3174008190a2b5bb1b061ea4df completed April 19, 2026, 5:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c650930081909de4b6ccdd43fbc3 completed June 19, 2026, 4:32 a.m.
NEDg Description generation batch_6a34c71d75b48190b3b47facc35ad833 completed June 19, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_6a34c7807d208190b7a50f84aa2b3058 completed June 19, 2026, 4:37 a.m.
Created at: April 10, 2026, 5:51 a.m.