Triple

T33061620
Position Surface form Disambiguated ID Type / Status
Subject Ryazan Kremlin E845987 entity
Predicate significantBuilding P1544 FINISHED
Object Belfry of the Ryazan Kremlin
The Belfry of the Ryazan Kremlin is a prominent historic bell tower and architectural landmark within the Ryazan Kremlin complex in Russia.
E845987 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: Belfry of the Ryazan Kremlin | Statement: [Ryazan Kremlin, significantBuilding, Belfry of the Ryazan Kremlin]
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: Belfry of the Ryazan Kremlin
Triple: [Ryazan Kremlin, significantBuilding, Belfry of the Ryazan Kremlin]
Generated description
The Belfry of the Ryazan Kremlin is a prominent historic bell tower and architectural landmark within the Ryazan Kremlin complex in Russia.

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_69f3495333b8819095e9af56855b9061 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d37a54cc8190a4f7819abb2ae52a completed May 3, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34f01025208190a7cae6408f47afad completed June 19, 2026, 7:30 a.m.
NEDg Description generation batch_6a34ffc9a2a48190992db5554d4c6b02 completed June 19, 2026, 8:37 a.m.
NED2 Entity disambiguation (via description) batch_6a35003c4d7c819099f0013b1bc3cafe completed June 19, 2026, 8:39 a.m.
Created at: May 1, 2026, 1:25 a.m.