Triple

T24894507
Position Surface form Disambiguated ID Type / Status
Subject Edirne Vilayet E623098 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Sanjak of Edirne
The Sanjak of Edirne was an Ottoman Empire administrative district centered on the historic city of Edirne in European Turkey.
E1688059 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: Sanjak of Edirne | Statement: [Edirne Vilayet, containsAdministrativeTerritorialEntity, Sanjak of Edirne]
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: Sanjak of Edirne
Triple: [Edirne Vilayet, containsAdministrativeTerritorialEntity, Sanjak of Edirne]
Generated description
The Sanjak of Edirne was an Ottoman Empire administrative district centered on the historic city of Edirne in European Turkey.

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_69e2fac597708190a922bf39a49ec70a completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f42346cddc81908691d5a6105fbd01 completed May 1, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10b715795481908c338dafa4a23eeb completed May 22, 2026, 8:05 p.m.
NEDg Description generation batch_6a10b9966114819093e81a647905346a completed May 22, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a10ba344df081908266aaa1920d9f3d completed May 22, 2026, 8:19 p.m.
Created at: April 18, 2026, 5:26 a.m.