Triple

T11161084
Position Surface form Disambiguated ID Type / Status
Subject Warmian-Masurian Voivodeship E264035 entity
Predicate containsRiver P165 FINISHED
Object Pasłęka
Pasłęka is a river in northern Poland that flows through the Warmian-Masurian region and is known for its natural landscapes and ecological value.
E980709 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: Pasłęka | Statement: [Warmian-Masurian Voivodeship, containsRiver, Pasłęka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pasłęka
Context triple: [Warmian-Masurian Voivodeship, containsRiver, Pasłęka]
  • A. Łęczna
    Łęczna is a town in eastern Poland known for its location near the Lublin Coal Basin and as a local administrative and service center.
  • B. Pszczyna
    Pszczyna is a historic town in southern Poland known for its well-preserved castle complex and picturesque old town.
  • C. Ciechocinek
    Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
  • D. Oleśnica
    Oleśnica is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
  • E. Oleśnica
    Oleśnica is a village located in Busko County in the Świętokrzyskie Voivodeship of south-central Poland.
  • 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: Pasłęka
Triple: [Warmian-Masurian Voivodeship, containsRiver, Pasłęka]
Generated description
Pasłęka is a river in northern Poland that flows through the Warmian-Masurian region and is known for its natural landscapes and ecological value.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pasłęka
Target entity description: Pasłęka is a river in northern Poland that flows through the Warmian-Masurian region and is known for its natural landscapes and ecological value.
  • A. Łęczna
    Łęczna is a town in eastern Poland known for its location near the Lublin Coal Basin and as a local administrative and service center.
  • B. Pszczyna
    Pszczyna is a historic town in southern Poland known for its well-preserved castle complex and picturesque old town.
  • C. Ciechocinek
    Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
  • D. Oleśnica
    Oleśnica is a historic town in southwestern Poland known for its Renaissance castle and well-preserved old town.
  • E. Oleśnica
    Oleśnica is a village located in Busko County in the Świętokrzyskie Voivodeship of south-central Poland.
  • 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_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8817a90819087820d5241c58851 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63449892881909d361815cbfcdee5 completed May 2, 2026, 5:28 p.m.
NEDg Description generation batch_69f635997b088190b6207fcac5594eb2 completed May 2, 2026, 5:34 p.m.
NED2 Entity disambiguation (via description) batch_69f636d727a08190882eec3fd664b64d completed May 2, 2026, 5:39 p.m.
Created at: April 8, 2026, 9:29 p.m.