Triple

T1051636
Position Surface form Disambiguated ID Type / Status
Subject Subcarpathian Voivodeship E22711 entity
Predicate contains P35 FINISHED
Object Krosno
Krosno is a historic town in southeastern Poland known for its glassmaking industry and well-preserved old town.
E217525 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: Krosno | Statement: [Subcarpathian Voivodeship, contains, Krosno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krosno
Context triple: [Subcarpathian Voivodeship, contains, Krosno]
  • A. Tarnów
    Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
  • B. Włoszczowa
    Włoszczowa is a town in south-central Poland known as the seat of Włoszczowa County and a local administrative and service center.
  • C. Ojców
    Ojców is a small village in southern Poland known as a gateway to the picturesque Ojców National Park in the Kraków-Częstochowa Upland.
  • D. Bielsko-Biała
    Bielsko-Biała is a city in southern Poland at the foot of the Beskid Mountains, known as a regional industrial and cultural center formed from the historic towns of Bielsko and Biała.
  • E. Chrzanów
    Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
  • 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: Krosno
Triple: [Subcarpathian Voivodeship, contains, Krosno]
Generated description
Krosno is a historic town in southeastern Poland known for its glassmaking industry and well-preserved old town.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Krosno
Target entity description: Krosno is a historic town in southeastern Poland known for its glassmaking industry and well-preserved old town.
  • A. Tarnów
    Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
  • B. Włoszczowa
    Włoszczowa is a town in south-central Poland known as the seat of Włoszczowa County and a local administrative and service center.
  • C. Ojców
    Ojców is a small village in southern Poland known as a gateway to the picturesque Ojców National Park in the Kraków-Częstochowa Upland.
  • D. Bielsko-Biała
    Bielsko-Biała is a city in southern Poland at the foot of the Beskid Mountains, known as a regional industrial and cultural center formed from the historic towns of Bielsko and Biała.
  • E. Chrzanów
    Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
  • 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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8b5312081909796df58fa7c1e9d completed March 1, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69adf3a5cac081908d655e42a58a81c5 completed March 8, 2026, 10:09 p.m.
NEDg Description generation batch_69adf55207248190bd903c7faa3729e7 completed March 8, 2026, 10:16 p.m.
NED2 Entity disambiguation (via description) batch_69adf5e074088190b6b383fb93cd18d8 completed March 8, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:42 p.m.