Triple
T35848940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | בוזי |
E1036292
|
entity |
| Predicate | associatedWithTextCorpus |
P8272
|
FINISHED |
| Object | המקרא |
—
|
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: המקרא | Statement: [בוזי, associatedWithTextCorpus, המקרא]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithTextCorpus Context triple: [בוזי, associatedWithTextCorpus, המקרא]
-
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.
relatedToAuthorCorpus
Indicates a general association or connection between something and the body of works (corpus) produced by a particular author.
-
C.
associatedWithText
chosen
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
-
D.
hasPartOfCorpus
Indicates that one entity constitutes a component or segment of the overall corpus associated with another entity.
-
E.
corpusEnhancedTo
Indicates that a corpus has been improved, expanded, or otherwise augmented to become another, enhanced version of that corpus.
- 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_69f76e1a29e8819088280f26096aeb55 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.