Triple

T894459
Position Surface form Disambiguated ID Type / Status
Subject Home Army E19311 entity
Predicate hasPart P35 FINISHED
Object Kedyw
Kedyw was a special operations and sabotage unit of the Polish underground Home Army that carried out resistance actions against Nazi German occupation during World War II.
 E106076 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: Kedyw | Statement: [Home Army, hasPart, Kedyw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kedyw
Context triple: [Home Army, hasPart, Kedyw]
  • A. Kawki
    Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
  • B. Kwatsáan
    Kwatsáan is the self-designation of the Quechan people, a Native American tribe traditionally living along the lower Colorado River in what is now southeastern California and southwestern Arizona.
  • C. Keda
    Keda is a small town and administrative center in the mountainous Adjara region of southwestern Georgia.
  • D. Wilella
    Wilella is the full given name of American novelist Willa Cather, renowned for her works depicting frontier life on the Great Plains.
  • E. Klecko
    Klecko is the surname of former American football defensive lineman Joe Klecko, best known for his standout career with the New York Jets as part of the “New York Sack Exchange.”
  • 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: Kedyw
Triple: [Home Army, hasPart, Kedyw]
Generated description
Kedyw was a special operations and sabotage unit of the Polish underground Home Army that carried out resistance actions against Nazi German occupation during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kedyw
Target entity description: Kedyw was a special operations and sabotage unit of the Polish underground Home Army that carried out resistance actions against Nazi German occupation during World War II.
  • A. Kawki
    Kawki is an indigenous Andean language closely related to Aymara and spoken by a small number of people in Peru.
  • B. Kwatsáan
    Kwatsáan is the self-designation of the Quechan people, a Native American tribe traditionally living along the lower Colorado River in what is now southeastern California and southwestern Arizona.
  • C. Keda
    Keda is a small town and administrative center in the mountainous Adjara region of southwestern Georgia.
  • D. Wilella
    Wilella is the full given name of American novelist Willa Cather, renowned for her works depicting frontier life on the Great Plains.
  • E. Klecko
    Klecko is the surname of former American football defensive lineman Joe Klecko, best known for his standout career with the New York Jets as part of the “New York Sack Exchange.”
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad22b6fc819093e655c8ce1f738b completed March 1, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c02772208190ac86dd885728e89c completed March 4, 2026, 5:16 a.m.
NEDg Description generation batch_69a7c2f036548190bc018c0cbe02d0ca completed March 4, 2026, 5:28 a.m.
NED2 Entity disambiguation (via description) batch_69a7c38925b481909133a1b098b08fa9 completed March 4, 2026, 5:30 a.m.
Created at: March 1, 2026, 7:39 p.m.