Triple

T34489679
Position Surface form Disambiguated ID Type / Status
Subject Vsevolod Nestayko E885430 entity
Predicate notableWork P4 FINISHED
Object In the Land of the Sunflower
"In the Land of the Sunflower" is a children's book by Ukrainian writer Vsevolod Nestayko, known for its imaginative storytelling and enduring popularity in Ukrainian children's literature.
E2098758 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: In the Land of the Sunflower | Statement: [Vsevolod Nestayko, notableWork, In the Land of the Sunflower]
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: In the Land of the Sunflower
Triple: [Vsevolod Nestayko, notableWork, In the Land of the Sunflower]
Generated description
"In the Land of the Sunflower" is a children's book by Ukrainian writer Vsevolod Nestayko, known for its imaginative storytelling and enduring popularity in Ukrainian children's literature.

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_69f349cafcec8190997b45b3fdc16c27 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71cecdf4481908ed4944223a24421 completed May 3, 2026, 10:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37213fc5ac819087b0d209e5081a65 completed June 20, 2026, 11:24 p.m.
NEDg Description generation batch_6a37221583e48190a3dbe0dc7ad27453 completed June 20, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_6a3722b425808190a8453a3e71d14066 completed June 20, 2026, 11:31 p.m.
Created at: May 1, 2026, 2:01 a.m.