Triple

T27978280
Position Surface form Disambiguated ID Type / Status
Subject cursed soldiers E706547 entity
Predicate participant P858 FINISHED
Object Danuta Siedzikówna
Danuta Siedzikówna was a young Polish Home Army nurse and member of the anti-communist underground, remembered as a symbol of resistance after being executed by the communist authorities following World War II.
E1802426 NE FINISHED

How this triple was built (2 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: Danuta Siedzikówna | Statement: [cursed soldiers, participant, Danuta Siedzikówna]
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: Danuta Siedzikówna
Triple: [cursed soldiers, participant, Danuta Siedzikówna]
Generated description
Danuta Siedzikówna was a young Polish Home Army nurse and member of the anti-communist underground, remembered as a symbol of resistance after being executed by the communist authorities following World War II.

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_69ef96b7f330819090f315318ba6977e completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63b661b8081908abaf92cde6ab125 completed May 2, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c8f495548190b62e660146962c5d completed May 26, 2026, 4:23 p.m.
NEDg Description generation batch_6a15ca1e992c819099d74611836ba016 completed May 26, 2026, 4:28 p.m.
NED2 Entity disambiguation (via description) batch_6a15cbdf46208190916381816f411f87 completed May 26, 2026, 4:35 p.m.
Created at: April 27, 2026, 7:42 p.m.