Triple

T4226627
Position Surface form Disambiguated ID Type / Status
Subject Sergo Zakariadze E94474 entity
Predicate givenName P17 FINISHED
Object Sergo
Sergo is a masculine given name, particularly common in Georgian and other Caucasian cultures.
 E422595 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: Sergo | Statement: [Sergo Zakariadze, givenName, Sergo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sergo
Context triple: [Sergo Zakariadze, givenName, Sergo]
  • A. Sebastos
    Sebastos was the grand artificial harbor of ancient Caesarea Maritima, renowned as one of the largest and most advanced seaports of the Roman world.
  • B. Lebbaeus
    Lebbaeus is an alternative name traditionally associated with the apostle Thaddaeus, one of the Twelve Apostles of Jesus in the New Testament.
  • C. Leonidio
    Leonidio is a traditional coastal town in the eastern Peloponnese of Greece, known for its dramatic red cliffs, Tsakonian cultural heritage, and popular rock-climbing routes.
  • D. Stylius
    Stylius is a consumer products brand likely focused on personal or household items within the Consumer Products Division’s portfolio.
  • E. Gavar
    Gavar is a town in Armenia that serves as a regional center near Lake Sevan in the Gegharkunik Province.
  • 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: Sergo
Triple: [Sergo Zakariadze, givenName, Sergo]
Generated description
Sergo is a masculine given name, particularly common in Georgian and other Caucasian cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sergo
Target entity description: Sergo is a masculine given name, particularly common in Georgian and other Caucasian cultures.
  • A. Sebastos
    Sebastos was the grand artificial harbor of ancient Caesarea Maritima, renowned as one of the largest and most advanced seaports of the Roman world.
  • B. Lebbaeus
    Lebbaeus is an alternative name traditionally associated with the apostle Thaddaeus, one of the Twelve Apostles of Jesus in the New Testament.
  • C. Leonidio
    Leonidio is a traditional coastal town in the eastern Peloponnese of Greece, known for its dramatic red cliffs, Tsakonian cultural heritage, and popular rock-climbing routes.
  • D. Stylius
    Stylius is a consumer products brand likely focused on personal or household items within the Consumer Products Division’s portfolio.
  • E. Gavar
    Gavar is a town in Armenia that serves as a regional center near Lake Sevan in the Gegharkunik Province.
  • 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_69b3453700a08190ae88792e3dc63207 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e4ed34c819081d1479ce87cd78c completed March 12, 2026, 11:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5964a388881908038e5a612424b9b completed March 14, 2026, 5:09 p.m.
NEDg Description generation batch_69b596cb73ac81909f83daca406ad8c4 completed March 14, 2026, 5:11 p.m.
NED2 Entity disambiguation (via description) batch_69b59a9c386081909c21ad554d403bfc completed March 14, 2026, 5:27 p.m.
Created at: March 12, 2026, 11:04 p.m.