Triple

T15795561
Position Surface form Disambiguated ID Type / Status
Subject ალექსანდრე ყაზბეგი E382967 entity
Predicate notableWork P4 FINISHED
Object „ელგუჯა“
„ელგუჯა“ არის ალექსანდრე ყაზბეგის სოციალური-რეალისტური რომანი, რომელიც აღწერს კავკასიური მთის საზოგადოების ყოფას, ტრადიციებსა და სოციალური უსამართლობის წინააღმდეგ ბრძოლას.
 E1176709 NE FINISHED

How this triple was built (4 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: „ელგუჯა“ | Statement: [ალექსანდრე ყაზბეგი, notableWork, „ელგუჯა“]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: „ელგუჯა“
Context triple: [ალექსანდრე ყაზბეგი, notableWork, „ელგუჯა“]
  • A. EGEL
    EGEL is the ICAO airport code for Coll Airport, a small airfield serving the island of Coll in Scotland.
  • B. EGUL
    EGUL is the ICAO airport code for RAF Lakenheath, a major Royal Air Force station in Suffolk, England that hosts United States Air Force operations.
  • C. Elp
    Elp is a small village in the Dutch province of Drenthe, known for its rural character and surrounding heathland landscapes.
  • D. ERGA
    ERGA is a European advisory body that brings together national regulators to help coordinate and harmonize audiovisual media regulation across the EU.
  • E. Yesügei
    Yesügei was a 12th-century Mongol chieftain of the Borjigin clan and the father of Genghis Khan.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: „ელგუჯა“
Triple: [ალექსანდრე ყაზბეგი, notableWork, „ელგუჯა“]
Generated description
„ელგუჯა“ არის ალექსანდრე ყაზბეგის სოციალური-რეალისტური რომანი, რომელიც აღწერს კავკასიური მთის საზოგადოების ყოფას, ტრადიციებსა და სოციალური უსამართლობის წინააღმდეგ ბრძოლას.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: „ელგუჯა“
Target entity description: „ელგუჯა“ არის ალექსანდრე ყაზბეგის სოციალური-რეალისტური რომანი, რომელიც აღწერს კავკასიური მთის საზოგადოების ყოფას, ტრადიციებსა და სოციალური უსამართლობის წინააღმდეგ ბრძოლას.
  • A. EGEL
    EGEL is the ICAO airport code for Coll Airport, a small airfield serving the island of Coll in Scotland.
  • B. EGUL
    EGUL is the ICAO airport code for RAF Lakenheath, a major Royal Air Force station in Suffolk, England that hosts United States Air Force operations.
  • C. Elp
    Elp is a small village in the Dutch province of Drenthe, known for its rural character and surrounding heathland landscapes.
  • D. ERGA
    ERGA is a European advisory body that brings together national regulators to help coordinate and harmonize audiovisual media regulation across the EU.
  • E. Yesügei
    Yesügei was a 12th-century Mongol chieftain of the Borjigin clan and the father of Genghis Khan.
  • F. None of above. chosen

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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4dc887081909d682ae153f06d97 completed April 16, 2026, 10:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff90aea81c8190ad8bc0cdedf4b77a completed May 9, 2026, 7:53 p.m.
NEDg Description generation batch_69ff93b24828819092841bc02059995d completed May 9, 2026, 8:06 p.m.
NED2 Entity disambiguation (via description) batch_69ff9435b800819093985b293a541e46 completed May 9, 2026, 8:08 p.m.
Created at: April 10, 2026, 4:48 a.m.