Triple

T17292755
Position Surface form Disambiguated ID Type / Status
Subject Nikola Kljusev E419827 entity
Predicate familyName P18 FINISHED
Object Kljusev
Kljusev is the surname of Nikola Kljusev, a prominent Macedonian economist and the first Prime Minister of independent Macedonia.
 E1260898 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: Kljusev | Statement: [Nikola Kljusev, familyName, Kljusev]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kljusev
Context triple: [Nikola Kljusev, familyName, Kljusev]
  • A. Kamenskiy
    Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
  • B. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • C. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • D. Lestkov
    Lestkov is a small municipality and village located in the Tachov District of the Plzeň Region in the Czech Republic.
  • E. Yuryatin
    Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
  • 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: Kljusev
Triple: [Nikola Kljusev, familyName, Kljusev]
Generated description
Kljusev is the surname of Nikola Kljusev, a prominent Macedonian economist and the first Prime Minister of independent Macedonia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kljusev
Target entity description: Kljusev is the surname of Nikola Kljusev, a prominent Macedonian economist and the first Prime Minister of independent Macedonia.
  • A. Kamenskiy
    Kamenskiy is a Slavic surname, commonly transliterated from Russian or related languages, borne by various individuals across Eastern Europe and the former Soviet Union.
  • B. Khovrino
    Khovrino is a Moscow Metro station serving as the northern terminus of the Zamoskvoretskaya Line.
  • C. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • D. Lestkov
    Lestkov is a small municipality and village located in the Tachov District of the Plzeň Region in the Czech Republic.
  • E. Yuryatin
    Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
  • 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_69d886db32608190a61e18862c5a8af6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e43785383881908ec61ddf5e2193cf completed April 19, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a017959ffb0819099d70ed1541158ee completed May 11, 2026, 6:38 a.m.
NEDg Description generation batch_6a017c9e99888190a99e3910c46d90c5 completed May 11, 2026, 6:52 a.m.
NED2 Entity disambiguation (via description) batch_6a017d340b988190a468753604150bd3 completed May 11, 2026, 6:54 a.m.
Created at: April 10, 2026, 5:40 a.m.