Triple

T224604
Position Surface form Disambiguated ID Type / Status
Subject Treblinka E4287 entity
Predicate locatedNear P294 FINISHED
Object Malkinia Górna
Małkinia Górna is a village in northeastern Poland that served as a key railway junction near the Treblinka extermination camp during World War II.
E28608 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: Malkinia Górna | Statement: [Treblinka, locatedNear, Malkinia Górna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malkinia Górna
Context triple: [Treblinka, locatedNear, Malkinia Górna]
  • A. Sucha Beskidzka
    Sucha Beskidzka is a small historic town in southern Poland, known for its picturesque Beskid mountain setting and its Renaissance-style castle.
  • B. Skawina
    Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
  • C. Beskid Sądecki
    Beskid Sądecki is a mountain range in southern Poland that forms part of the Western Beskids, known for its forested peaks, spa towns, and hiking trails.
  • D. Bochnia
    Bochnia is a historic town in southern Poland best known for its medieval salt mine, one of the oldest in Europe.
  • E. Wieliczka
    Wieliczka is a historic town in southern Poland best known for its UNESCO-listed medieval salt mine, one of the country’s major tourist attractions.
  • 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: Malkinia Górna
Triple: [Treblinka, locatedNear, Malkinia Górna]
Generated description
Małkinia Górna is a village in northeastern Poland that served as a key railway junction near the Treblinka extermination camp during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Malkinia Górna
Target entity description: Małkinia Górna is a village in northeastern Poland that served as a key railway junction near the Treblinka extermination camp during World War II.
  • A. Sucha Beskidzka
    Sucha Beskidzka is a small historic town in southern Poland, known for its picturesque Beskid mountain setting and its Renaissance-style castle.
  • B. Skawina
    Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
  • C. Beskid Sądecki
    Beskid Sądecki is a mountain range in southern Poland that forms part of the Western Beskids, known for its forested peaks, spa towns, and hiking trails.
  • D. Bochnia
    Bochnia is a historic town in southern Poland best known for its medieval salt mine, one of the oldest in Europe.
  • E. Wieliczka
    Wieliczka is a historic town in southern Poland best known for its UNESCO-listed medieval salt mine, one of the country’s major tourist attractions.
  • 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c8c0b8881908016161568c0cbfb completed Feb. 28, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69a35277532c8190ab2815c63a564e33 completed Feb. 28, 2026, 8:39 p.m.
NEDg Description generation batch_69a3547eeef88190923f3d7b46e11d7e completed Feb. 28, 2026, 8:47 p.m.
NED2 Entity disambiguation (via description) batch_69a354f267ac8190ace99e80f7c24d45 completed Feb. 28, 2026, 8:49 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.