Triple

T1456305
Position Surface form Disambiguated ID Type / Status
Subject Lower Silesia E31408 entity
Predicate contains P35 FINISHED
Object Świdnica
Świdnica is a historic town in southwestern Poland known for its well-preserved medieval architecture and the UNESCO-listed Church of Peace.
 E311312 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: Świdnica | Statement: [Lower Silesia, contains, Świdnica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Świdnica
Context triple: [Lower Silesia, contains, Świdnica]
  • A. Cieszyn
    Cieszyn is a historic town in southern Poland on the Olza River, known for its shared Polish-Czech heritage and well-preserved old town.
  • B. Tarnów
    Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
  • 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. Legnica
    Legnica is a historic city in southwestern Poland known for its medieval architecture, including a prominent castle and old town, and its role as a regional cultural and economic center.
  • E. Włoszczowa
    Włoszczowa is a town in south-central Poland known as the seat of Włoszczowa County and a local administrative and service 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: Świdnica
Triple: [Lower Silesia, contains, Świdnica]
Generated description
Świdnica is a historic town in southwestern Poland known for its well-preserved medieval architecture and the UNESCO-listed Church of Peace.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Świdnica
Target entity description: Świdnica is a historic town in southwestern Poland known for its well-preserved medieval architecture and the UNESCO-listed Church of Peace.
  • A. Cieszyn
    Cieszyn is a historic town in southern Poland on the Olza River, known for its shared Polish-Czech heritage and well-preserved old town.
  • B. Tarnów
    Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
  • 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. Legnica
    Legnica is a historic city in southwestern Poland known for its medieval architecture, including a prominent castle and old town, and its role as a regional cultural and economic center.
  • E. Włoszczowa
    Włoszczowa is a town in south-central Poland known as the seat of Włoszczowa County and a local administrative and service 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c581714881909bf4c2bad9645176 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b085fc357481908259683cb4860cf3 completed March 10, 2026, 8:58 p.m.
NEDg Description generation batch_69b0d499cf108190beee4b64d88e9f3d completed March 11, 2026, 2:34 a.m.
NED2 Entity disambiguation (via description) batch_69b0d4fbdc7481909307e569b1874fe0 completed March 11, 2026, 2:35 a.m.
Created at: March 1, 2026, 8 p.m.