Triple
T157571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisdom Literature |
E3211
|
entity |
| Predicate | associatedWithLanguage |
P2830
|
FINISHED |
| Object | Hebrew |
—
|
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: Hebrew | Statement: [Wisdom Literature, associatedWithLanguage, Hebrew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithLanguage Context triple: [Wisdom Literature, associatedWithLanguage, Hebrew]
-
A.
includesLanguage
Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
-
B.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
C.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
D.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
-
E.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a25830136881909f5ecb2cb22097b2 |
completed | Feb. 28, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69a2565f30848190a2a71fdb7dc140b5 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.