Triple

T28126644
Position Surface form Disambiguated ID Type / Status
Subject Siege of Adrianople E710945 entity
Predicate commanderForOttomanEmpire P23718 FINISHED
Object Mehmed Şükrü Pasha
Mehmed Şükrü Pasha was an Ottoman military commander best known for leading the defense of Adrianople (Edirne) during the First Balkan War.
E1820260 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: Mehmed Şükrü Pasha | Statement: [Siege of Adrianople, commanderForOttomanEmpire, Mehmed Şükrü 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: Mehmed Şükrü Pasha
Triple: [Siege of Adrianople, commanderForOttomanEmpire, Mehmed Şükrü Pasha]
Generated description
Mehmed Şükrü Pasha was an Ottoman military commander best known for leading the defense of Adrianople (Edirne) during the First Balkan War.

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_69ef9b73bd288190a21ae3d6aa14f386 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f640fd4f1c8190906450e47fb29281 completed May 2, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a164161680c81908f424523d5cea326 completed May 27, 2026, 12:57 a.m.
NEDg Description generation batch_6a164360a9d08190adf3fa50148b8cd2 completed May 27, 2026, 1:05 a.m.
NED2 Entity disambiguation (via description) batch_6a1644905e208190ad43890b9dbda231 completed May 27, 2026, 1:10 a.m.
Created at: April 27, 2026, 9:20 p.m.