Triple

T23708396
Position Surface form Disambiguated ID Type / Status
Subject Jan Amor Tarnowski E585793 entity
Predicate positionHeld P8 FINISHED
Object Starost of Ropczyce
The Starost of Ropczyce was a local royal-appointed administrative and judicial official governing the Ropczyce district in the Kingdom of Poland.
E1610695 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: Starost of Ropczyce | Statement: [Jan Amor Tarnowski, positionHeld, Starost of Ropczyce]
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: Starost of Ropczyce
Triple: [Jan Amor Tarnowski, positionHeld, Starost of Ropczyce]
Generated description
The Starost of Ropczyce was a local royal-appointed administrative and judicial official governing the Ropczyce district in the Kingdom of Poland.

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_69e24905f77881908194d645676acd60 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b68868ac8190824cdd7eb9fb2f06 completed April 29, 2026, 7:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f760037608190b049108d95311941 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f77cae9dc8190b324ac8deeac83c4 completed May 21, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78df8c9c81908eb3912b212862f9 completed May 21, 2026, 9:27 p.m.
Created at: April 17, 2026, 6:53 p.m.