Triple

T17840179
Position Surface form Disambiguated ID Type / Status
Subject Jasło E445501 entity
Predicate twinTown P1072 FINISHED
Object Humenne
Humenné is a town in eastern Slovakia known for its historic manor house, surrounding Carpathian landscape, and role as a regional cultural and economic center.
 E1290513 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: Humenne | Statement: [Jasło, twinTown, Humenne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Humenne
Context triple: [Jasło, twinTown, Humenne]
  • A. Hannen
    Hannen is an English surname associated with several notable figures, including actors and judges, in British history.
  • B. Henniez
    Henniez is a small municipality in the canton of Vaud, Switzerland, best known for its natural mineral water brand of the same name.
  • C. Hanem
    Hanem is an Ottoman-era honorific title used for women of high social standing, similar to "lady" or "madam."
  • D. Hennenman
    Hennenman is a small town in South Africa’s Free State province, situated within the Lejweleputswa District and known historically for its links to the regional mining and agricultural economy.
  • E. Hedebrant
    Hedebrant is a Swedish surname most notably borne by actor Kåre Hedebrant, known for his role in the film "Let the Right One In."
  • 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: Humenne
Triple: [Jasło, twinTown, Humenne]
Generated description
Humenné is a town in eastern Slovakia known for its historic manor house, surrounding Carpathian landscape, and role as a regional cultural and economic center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Humenne
Target entity description: Humenné is a town in eastern Slovakia known for its historic manor house, surrounding Carpathian landscape, and role as a regional cultural and economic center.
  • A. Hannen
    Hannen is an English surname associated with several notable figures, including actors and judges, in British history.
  • B. Henniez
    Henniez is a small municipality in the canton of Vaud, Switzerland, best known for its natural mineral water brand of the same name.
  • C. Hanem
    Hanem is an Ottoman-era honorific title used for women of high social standing, similar to "lady" or "madam."
  • D. Hennenman
    Hennenman is a small town in South Africa’s Free State province, situated within the Lejweleputswa District and known historically for its links to the regional mining and agricultural economy.
  • E. Hedebrant
    Hedebrant is a Swedish surname most notably borne by actor Kåre Hedebrant, known for his role in the film "Let the Right One In."
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d2a570c81909787296bde7e795c completed April 19, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0306fc77fc8190972cf34f094720ac completed May 12, 2026, 10:54 a.m.
NEDg Description generation batch_6a030789a4408190bfbbb205fe7235a8 completed May 12, 2026, 10:57 a.m.
NED2 Entity disambiguation (via description) batch_6a03082e3e0c8190b898e076bb264b3c completed May 12, 2026, 10:59 a.m.
Created at: April 10, 2026, 10:16 a.m.