Triple
T26349330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osmanlı'da Şehir ve Toplum |
E662859
|
entity |
| Predicate | bölümİçerik |
P3120
|
FINISHED |
| Object | çeşitli makale ve incelemelerden oluşur |
—
|
LITERAL 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: çeşitli makale ve incelemelerden oluşur | Statement: [Osmanlı'da Şehir ve Toplum, bölümİçerik, çeşitli makale ve incelemelerden oluşur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bölümİçerik Context triple: [Osmanlı'da Şehir ve Toplum, bölümİçerik, çeşitli makale ve incelemelerden oluşur]
-
A.
contentIs
Indicates that one entity serves as, or is equivalent to, the content contained within another entity.
-
B.
articleContent
Indicates that one entity is the textual or media content that makes up the body of another entity, typically an article or document.
-
C.
article2Content
Indicates that one article serves as the content or body text for another article or higher-level publication entity.
-
D.
partitionIContent
Indicates that a larger content item is divided into distinct internal parts or segments that collectively make up its whole.
-
E.
section
chosen
Indicates that one entity is a distinct part, division, or segment of another entity within a larger whole.
- F. None of above.
Provenance (3 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. |
| PD | Predicate disambiguation | batch_69f5f800fa9c8190aab0962669fde8ac |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 10:44 p.m.