Triple

T26595903
Position Surface form Disambiguated ID Type / Status
Subject Köprülü Mehmed Pasha E667488 entity
Predicate predecessor P97 FINISHED
Object Boynuyaralı Mehmed Pasha
Boynuyaralı Mehmed Pasha was an Ottoman statesman who served as grand vizier in the mid-17th century, immediately before the influential Köprülü Mehmed Pasha.
E1787656 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: Boynuyaralı Mehmed Pasha | Statement: [Köprülü Mehmed Pasha, predecessor, Boynuyaralı Mehmed Pasha]
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: Boynuyaralı Mehmed Pasha
Triple: [Köprülü Mehmed Pasha, predecessor, Boynuyaralı Mehmed Pasha]
Generated description
Boynuyaralı Mehmed Pasha was an Ottoman statesman who served as grand vizier in the mid-17th century, immediately before the influential Köprülü Mehmed Pasha.

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_69ee9cfc385081909ac9ae178030a06e completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f61529a5748190896ba1a1d19aeaa1 completed May 2, 2026, 3:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e42b7bf88190bfb6e7179099d259 completed May 24, 2026, 11:42 a.m.
NEDg Description generation batch_6a12e4bc42e081909864bb2839e08143 completed May 24, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a12e551ec288190b818e25bf2e62f45 completed May 24, 2026, 11:47 a.m.
Created at: April 27, 2026, 2:10 a.m.