Triple

T26349876
Position Surface form Disambiguated ID Type / Status
Subject Eyüpsultan E662873 entity
Predicate administrativeCenter P1474 FINISHED
Object Eyüp Sultan Municipality building
The Eyüp Sultan Municipality building is the main governmental headquarters where the local administration of Istanbul’s historic Eyüpsultan district conducts its official and public services.
E1720999 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: Eyüp Sultan Municipality building | Statement: [Eyüpsultan, administrativeCenter, Eyüp Sultan Municipality building]
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: Eyüp Sultan Municipality building
Triple: [Eyüpsultan, administrativeCenter, Eyüp Sultan Municipality building]
Generated description
The Eyüp Sultan Municipality building is the main governmental headquarters where the local administration of Istanbul’s historic Eyüpsultan district conducts its official and public services.

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_69ee8130fc44819094e5ab1da201cd7b completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60fa9dc9c8190b2501a3bc23eabfe completed May 2, 2026, 2:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a119a66306c8190a33754abfa747dda completed May 23, 2026, 12:15 p.m.
NEDg Description generation batch_6a119b1444008190a4cdcbe5fd8bca98 completed May 23, 2026, 12:18 p.m.
NED2 Entity disambiguation (via description) batch_6a119c370ec481909db25ac02d20efd2 completed May 23, 2026, 12:23 p.m.
Created at: April 26, 2026, 10:44 p.m.