Triple

T6356041
Position Surface form Disambiguated ID Type / Status
Subject Zemst E142992 entity
Predicate hasAdministrativeCenter P1474 FINISHED
Object Zemst (town)
Zemst is a municipality and town in the Belgian province of Flemish Brabant, situated between Brussels and Mechelen.
 E589197 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: Zemst (town) | Statement: [Zemst, hasAdministrativeCenter, Zemst (town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zemst (town)
Context triple: [Zemst, hasAdministrativeCenter, Zemst (town)]
  • A. Dzerzhinovo
    Dzerzhinovo is a village in present-day Belarus best known as the birthplace of Soviet statesman and secret police founder Felix Dzerzhinsky.
  • B. Zemtsov
    Zemtsov is a Russian surname most notably borne by violist Mikhail Zemtsov.
  • C. Zemunik Donji
    Zemunik Donji is a village and municipality in Zadar County, Croatia, known for hosting the region’s main airport and a Croatian Air Force base.
  • D. Mikhaylovka
    Mikhaylovka is a city in southwestern Russia known as one of the key urban centers of Volgograd Oblast.
  • E. Kuznetsovo
    Kuznetsovo is the former name of the town now known as Belogorsk in Russia’s Amur Oblast.
  • 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: Zemst (town)
Triple: [Zemst, hasAdministrativeCenter, Zemst (town)]
Generated description
Zemst is a municipality and town in the Belgian province of Flemish Brabant, situated between Brussels and Mechelen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zemst (town)
Target entity description: Zemst is a municipality and town in the Belgian province of Flemish Brabant, situated between Brussels and Mechelen.
  • A. Dzerzhinovo
    Dzerzhinovo is a village in present-day Belarus best known as the birthplace of Soviet statesman and secret police founder Felix Dzerzhinsky.
  • B. Zemtsov
    Zemtsov is a Russian surname most notably borne by violist Mikhail Zemtsov.
  • C. Zemunik Donji
    Zemunik Donji is a village and municipality in Zadar County, Croatia, known for hosting the region’s main airport and a Croatian Air Force base.
  • D. Mikhaylovka
    Mikhaylovka is a city in southwestern Russia known as one of the key urban centers of Volgograd Oblast.
  • E. Kuznetsovo
    Kuznetsovo is the former name of the town now known as Belogorsk in Russia’s Amur Oblast.
  • 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_69c008d7a9c4819098d647ec47776917 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067e22c00819089bc68efb85bc2c8 completed March 22, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d5966a88190a7184157b235b170 completed March 27, 2026, 7:10 a.m.
NEDg Description generation batch_69c62f5da47081908c995e28ba2ee3f8 completed March 27, 2026, 7:18 a.m.
NED2 Entity disambiguation (via description) batch_69c62fd9dd4c819091e0d87259f9d60f completed March 27, 2026, 7:20 a.m.
Created at: March 22, 2026, 4:32 p.m.