Triple

T17162882
Position Surface form Disambiguated ID Type / Status
Subject Bielany E416525 entity
Predicate contains P35 FINISHED
Object Las Bielański
Las Bielański is a historic forest and nature reserve in Warsaw, Poland, known for its rich biodiversity and popular recreational paths.
E1253559 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: Las Bielański | Statement: [Bielany, contains, Las Bielański]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Las Bielański
Context triple: [Bielany, contains, Las Bielański]
  • A. Bielecki
    Bielecki is a Polish surname borne by various notable individuals across fields such as politics, sports, and mountaineering.
  • B. Daszyński
    Daszyński is a Polish surname most notably associated with Ignacy Daszyński, a prominent socialist politician and early leader in independent Poland.
  • C. Wasilewski
    Wasilewski is a Polish surname, typically indicating familial or geographic origin and commonly found in Poland and among the Polish diaspora.
  • D. Horsztyński
    "Horsztyński" is a dramatic work by Polish Romantic poet and playwright Juliusz Słowacki, reflecting his characteristic themes of patriotism, inner conflict, and national struggle.
  • E. Korzeniowski
    Korzeniowski is a Polish surname most notably borne by contemporary film and television composer Abel Korzeniowski.
  • 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: Las Bielański
Triple: [Bielany, contains, Las Bielański]
Generated description
Las Bielański is a historic forest and nature reserve in Warsaw, Poland, known for its rich biodiversity and popular recreational paths.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Las Bielański
Target entity description: Las Bielański is a historic forest and nature reserve in Warsaw, Poland, known for its rich biodiversity and popular recreational paths.
  • A. Bielecki
    Bielecki is a Polish surname borne by various notable individuals across fields such as politics, sports, and mountaineering.
  • B. Daszyński
    Daszyński is a Polish surname most notably associated with Ignacy Daszyński, a prominent socialist politician and early leader in independent Poland.
  • C. Wasilewski
    Wasilewski is a Polish surname, typically indicating familial or geographic origin and commonly found in Poland and among the Polish diaspora.
  • D. Horsztyński
    "Horsztyński" is a dramatic work by Polish Romantic poet and playwright Juliusz Słowacki, reflecting his characteristic themes of patriotism, inner conflict, and national struggle.
  • E. Korzeniowski
    Korzeniowski is a Polish surname most notably borne by contemporary film and television composer Abel Korzeniowski.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f91316108190b0d856d6fa5cd509 completed April 18, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01483969a48190a90268c9560b8cd7 completed May 11, 2026, 3:08 a.m.
NEDg Description generation batch_6a01495169d4819093962a3b4a97c47a completed May 11, 2026, 3:13 a.m.
NED2 Entity disambiguation (via description) batch_6a0149be8b888190bab95b612aad590a completed May 11, 2026, 3:15 a.m.
Created at: April 10, 2026, 5:37 a.m.