Triple

T25892969
Position Surface form Disambiguated ID Type / Status
Subject Abastumani Astrophysical Observatory E652385 entity
Predicate foundedBy P104 FINISHED
Object Evgeni Kharadze
Evgeni Kharadze was a prominent Georgian astronomer and academic who played a key role in developing astrophysical research in Georgia during the 20th century.
E1699363 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: Evgeni Kharadze | Statement: [Abastumani Astrophysical Observatory, foundedBy, Evgeni Kharadze]
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: Evgeni Kharadze
Triple: [Abastumani Astrophysical Observatory, foundedBy, Evgeni Kharadze]
Generated description
Evgeni Kharadze was a prominent Georgian astronomer and academic who played a key role in developing astrophysical research in Georgia during the 20th century.

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_69e7ab3c6cc081908de59bfcc28ec19d completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6037fe4348190a673fd5e7380087b completed May 2, 2026, 2 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecc0ace4819093937aa83ffc1913 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10ed2166748190bdc01176cb5f675c completed May 22, 2026, 11:56 p.m.
NED2 Entity disambiguation (via description) batch_6a10edb1ca0c81909f567f40e6601be6 completed May 22, 2026, 11:58 p.m.
Created at: April 22, 2026, 8:22 a.m.