Triple
T18724374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BERT |
E457858
|
entity |
| Predicate | trainingCorpus |
P21227
|
FINISHED |
| Object | BooksCorpus |
—
|
NE NERFINISHED |
How this triple was built (3 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: BooksCorpus | Statement: [BERT, trainingCorpus, BooksCorpus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BooksCorpus Context triple: [BERT, trainingCorpus, BooksCorpus]
-
A.
Word Books
Word Books was a Christian publishing company known for producing religious and inspirational literature.
-
B.
الكتاب
الكتاب هو مؤلَّف نحوي كلاسيكي لسيبويه يُعدّ من أهم وأقدم المراجع في النحو العربي.
-
C.
BookCorpus
chosen
BookCorpus is a large collection of freely available books commonly used as a pretraining dataset for natural language processing models.
-
D.
Books Division
The Books Division is the publishing arm of the University of Chicago Press responsible for producing and distributing its scholarly and general-interest books.
-
E.
Buchs
Buchs is a municipality in the canton of St. Gallen in northeastern Switzerland, known as an industrial and commercial center near the Liechtenstein border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainingCorpus Context triple: [BERT, trainingCorpus, BooksCorpus]
-
A.
corpus
Indicates that an entity is a collection or body of texts, documents, or linguistic data used as a unified set for analysis or reference.
-
B.
trainingDataSource
Indicates the origin or provider from which the training data for a model or system is obtained.
-
C.
trainingDataType
Indicates the type or category of data used for training a model, system, or process.
-
D.
trainingUse
Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
-
E.
trainingDataIncludes
chosen
Indicates that one entity’s training dataset contains or incorporates the other entity as part of its data.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56abcfc048190a01dee959e768768 |
completed | April 19, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:50 a.m.