Triple

T612746
Position Surface form Disambiguated ID Type / Status
Subject Gdynia E12134 entity
Predicate hasDistrict P459 FINISHED
Object Orłowo
Orłowo is a coastal district of Gdynia in northern Poland, known for its scenic cliffs, pier, and Baltic Sea beaches.
 E78629 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: Orłowo | Statement: [Gdynia, hasDistrict, Orłowo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Orłowo
Context triple: [Gdynia, hasDistrict, Orłowo]
  • A. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • B. Mierzanowo
    Mierzanowo is a village in Poland notable as the birthplace of Ignacy Mościcki, the country's pre-World War II president and chemist.
  • C. Wadowice
    Wadowice is a historic town in southern Poland best known as the birthplace of Pope John Paul II.
  • D. Chrzanów
    Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
  • E. Płońsk
    Płońsk is a historic town in north-central Poland, known as the birthplace of Israel’s first prime minister, David Ben-Gurion.
  • 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: Orłowo
Triple: [Gdynia, hasDistrict, Orłowo]
Generated description
Orłowo is a coastal district of Gdynia in northern Poland, known for its scenic cliffs, pier, and Baltic Sea beaches.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Orłowo
Target entity description: Orłowo is a coastal district of Gdynia in northern Poland, known for its scenic cliffs, pier, and Baltic Sea beaches.
  • A. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • B. Mierzanowo
    Mierzanowo is a village in Poland notable as the birthplace of Ignacy Mościcki, the country's pre-World War II president and chemist.
  • C. Wadowice
    Wadowice is a historic town in southern Poland best known as the birthplace of Pope John Paul II.
  • D. Chrzanów
    Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
  • E. Płońsk
    Płońsk is a historic town in north-central Poland, known as the birthplace of Israel’s first prime minister, David Ben-Gurion.
  • 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_69a493309df48190a327f748e88049a6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49e08dbf88190ab050078a63e266b completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5693312888190bdf7bfa120d22520 completed March 2, 2026, 10:40 a.m.
NEDg Description generation batch_69a569ddf64c819080b1ab05601dcd0e completed March 2, 2026, 10:43 a.m.
NED2 Entity disambiguation (via description) batch_69a56a5b06748190a21259067d0b2c20 completed March 2, 2026, 10:45 a.m.
Created at: March 1, 2026, 7:35 p.m.