Triple

T33820690
Position Surface form Disambiguated ID Type / Status
Subject Lubomirski family E866817 entity
Predicate hasNotableMember P304 FINISHED
Object Antoni Benedykt Lubomirski
Antoni Benedykt Lubomirski was a Polish nobleman and magnate from the influential Lubomirski family who held high offices in the Polish–Lithuanian Commonwealth.
E2097180 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: Antoni Benedykt Lubomirski | Statement: [Lubomirski family, hasNotableMember, Antoni Benedykt Lubomirski]
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: Antoni Benedykt Lubomirski
Triple: [Lubomirski family, hasNotableMember, Antoni Benedykt Lubomirski]
Generated description
Antoni Benedykt Lubomirski was a Polish nobleman and magnate from the influential Lubomirski family who held high offices in the Polish–Lithuanian Commonwealth.

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_69f34991dd248190a659541588506b3c completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fffc48c08190b80a2bffddf50fb3 completed May 3, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3718116c9881908b482f0ea872d1c3 completed June 20, 2026, 10:45 p.m.
NEDg Description generation batch_6a37194415288190aa91266fca5cd697 completed June 20, 2026, 10:50 p.m.
NED2 Entity disambiguation (via description) batch_6a371a11d1088190a9156de452da374b completed June 20, 2026, 10:54 p.m.
Created at: May 1, 2026, 1:46 a.m.