Triple

T28161259
Position Surface form Disambiguated ID Type / Status
Subject Prince Konstantin of Yaroslavl E714900 entity
Predicate positionHeld P8 FINISHED
Object Prince of Yaroslavl
The Prince of Yaroslavl was the medieval ruler of the Yaroslavl principality in northeastern Rus', holding both political and military authority over the region.
E1847274 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: Prince of Yaroslavl | Statement: [Prince Konstantin of Yaroslavl, positionHeld, Prince of Yaroslavl]
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: Prince of Yaroslavl
Triple: [Prince Konstantin of Yaroslavl, positionHeld, Prince of Yaroslavl]
Generated description
The Prince of Yaroslavl was the medieval ruler of the Yaroslavl principality in northeastern Rus', holding both political and military authority over the region.

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_69efd6b156448190bfa15958208395c3 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f641eb9eec8190a50b58f0f28983b8 completed May 2, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f4220448190920ea22955f0dba0 completed June 7, 2026, 7:35 a.m.
NEDg Description generation batch_6a25242352f08190805e663c6bb680cc completed June 7, 2026, 7:56 a.m.
NED2 Entity disambiguation (via description) batch_6a2527e464508190a8e46b839fca593d completed June 7, 2026, 8:12 a.m.
Created at: April 27, 2026, 10:06 p.m.