Triple
T13451394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heavenly court |
E320614
|
entity |
| Predicate | relatedTermLanguage |
P76956
|
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: [Heavenly court, relatedTermLanguage, Hebrew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedTermLanguage Context triple: [Heavenly court, relatedTermLanguage, Hebrew]
-
A.
linkedToLanguage
Indicates that an entity has an association or connection with a specific language, such as being expressed in, related to, or dependent on that language.
-
B.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
C.
termLanguage
chosen
Indicates the language in which a given term is expressed or defined.
-
D.
closelyAssociatedLanguage
Indicates that one language is closely connected to another, such as through frequent co-use, mutual influence, or strong cultural or regional association.
-
E.
officialTermLanguage
Indicates the language in which an official term is formally expressed or defined.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaef973b08190a3d7fe1c2a913cff |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:41 p.m.