Triple

T7263142
Position Surface form Disambiguated ID Type / Status
Subject Warsaw metropolitan area E159704 entity
Predicate containsCity P294 FINISHED
Object Legionowo
Legionowo is a commuter city in east-central Poland that functions as a suburban satellite of Warsaw within its metropolitan area.
 E652755 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: Legionowo | Statement: [Warsaw metropolitan area, containsCity, Legionowo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Legionowo
Context triple: [Warsaw metropolitan area, containsCity, Legionowo]
  • A. Piła
    Piła is a city in northwestern Poland known as a regional economic and transport center in the Greater Poland Voivodeship.
  • B. Strzelno
    Strzelno is a town in north-central Poland best known as the birthplace of Nobel Prize–winning physicist Albert A. Michelson.
  • C. Łeba
    Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
  • D. Mrągowo
    Mrągowo is a picturesque town in northeastern Poland known for its lakeside setting and popular summer cultural and music festivals.
  • E. Ostrołęka
    Ostrołęka is a town in east-central Poland known for its historical role in the Napoleonic Wars and 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: Legionowo
Triple: [Warsaw metropolitan area, containsCity, Legionowo]
Generated description
Legionowo is a commuter city in east-central Poland that functions as a suburban satellite of Warsaw within its metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Legionowo
Target entity description: Legionowo is a commuter city in east-central Poland that functions as a suburban satellite of Warsaw within its metropolitan area.
  • A. Piła
    Piła is a city in northwestern Poland known as a regional economic and transport center in the Greater Poland Voivodeship.
  • B. Strzelno
    Strzelno is a town in north-central Poland best known as the birthplace of Nobel Prize–winning physicist Albert A. Michelson.
  • C. Łeba
    Łeba is a river in northern Poland that flows through the Pomeranian region to the Baltic Sea.
  • D. Mrągowo
    Mrągowo is a picturesque town in northeastern Poland known for its lakeside setting and popular summer cultural and music festivals.
  • E. Ostrołęka
    Ostrołęka is a town in east-central Poland known for its historical role in the Napoleonic Wars and 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_69c68838f9948190875fd60b2351230c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eac9fab88190881ab9e1cd94cdc1 completed March 27, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d3c3bfb48190877ba03ab0851a68 completed March 28, 2026, 1:12 p.m.
NEDg Description generation batch_69c7d44f36e881909d107cc625ebcfca completed March 28, 2026, 1:14 p.m.
NED2 Entity disambiguation (via description) batch_69c7d4cc3e78819098eb8ccfe7c42cc5 completed March 28, 2026, 1:17 p.m.
Created at: March 27, 2026, 2:57 p.m.