Triple

T34628797
Position Surface form Disambiguated ID Type / Status
Subject Kazasker Mustafa İzzet Efendi E889213 entity
Predicate positionHeld P8 FINISHED
Object Kazasker of Anatolia
The Kazasker of Anatolia was one of the two chief military judges of the Ottoman Empire, responsible for overseeing judicial and legal affairs in the empire’s Anatolian provinces.
E2106865 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: Kazasker of Anatolia | Statement: [Kazasker Mustafa İzzet Efendi, positionHeld, Kazasker of Anatolia]
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: Kazasker of Anatolia
Triple: [Kazasker Mustafa İzzet Efendi, positionHeld, Kazasker of Anatolia]
Generated description
The Kazasker of Anatolia was one of the two chief military judges of the Ottoman Empire, responsible for overseeing judicial and legal affairs in the empire’s Anatolian provinces.

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_69f349d64a388190a013cfa9bd33fad7 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7226727088190800a8d965710db93 completed May 3, 2026, 10:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3748e8ef008190aae7c90739d49e3b completed June 21, 2026, 2:14 a.m.
NEDg Description generation batch_6a3749d08ff48190b252be336b564065 completed June 21, 2026, 2:17 a.m.
NED2 Entity disambiguation (via description) batch_6a374dbedf148190bc1b24d470fd2224 completed June 21, 2026, 2:34 a.m.
Created at: May 1, 2026, 2:04 a.m.