Triple

T24155633
Position Surface form Disambiguated ID Type / Status
Subject Bolesław Orliński E598669 entity
Predicate familyName P18 FINISHED
Object Orliński
Orliński is a Polish surname most notably associated with Bolesław Orliński, a pioneering Polish aviator and military pilot.
E1624433 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: Orliński | Statement: [Bolesław Orliński, familyName, Orliński]
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: Orliński
Triple: [Bolesław Orliński, familyName, Orliński]
Generated description
Orliński is a Polish surname most notably associated with Bolesław Orliński, a pioneering Polish aviator and military pilot.

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_69e288cb0a3081909ef221744f274384 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e0e4fc9c8190bafabb4f08a2db45 completed April 29, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd0839c88190a3fc9fa2c0c96108 completed May 22, 2026, 2:18 a.m.
NEDg Description generation batch_6a0fbec907148190832159960dc4bdd6 completed May 22, 2026, 2:26 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbf3cf7988190a9d766bfca4ef994 completed May 22, 2026, 2:28 a.m.
Created at: April 17, 2026, 11:31 p.m.