Triple

T27349018
Position Surface form Disambiguated ID Type / Status
Subject Stefan Czarniecki E684304 entity
Predicate spouse P13 FINISHED
Object Zofia Kobierzycka
Zofia Kobierzycka was a Polish noblewoman best known as the wife of the 17th-century military commander and national hero Stefan Czarniecki.
 E1787753 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: Zofia Kobierzycka | Statement: [Stefan Czarniecki, spouse, Zofia Kobierzycka]
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: Zofia Kobierzycka
Triple: [Stefan Czarniecki, spouse, Zofia Kobierzycka]
Generated description
Zofia Kobierzycka was a Polish noblewoman best known as the wife of the 17th-century military commander and national hero Stefan Czarniecki.

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_69ef1480a76481908684256ddd5bfda3 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62ba5a110819092fe773ade8fec2e completed May 2, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ec8f9e24819091bdc4db4a4fd68d completed May 24, 2026, 12:18 p.m.
NEDg Description generation batch_6a12ed0fc060819085a0872a16a4badf completed May 24, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a12ed9d47988190a62268071859ede2 completed May 24, 2026, 12:22 p.m.
Created at: April 27, 2026, 11:47 a.m.