Triple
T6074409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dana |
E135363
|
entity |
| Predicate | meaningInHebrew |
P60525
|
FINISHED |
| Object | “arbiter” or “judge” (from the root דין / din) |
—
|
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: “arbiter” or “judge” (from the root דין / din) | Statement: [Dana, meaningInHebrew, “arbiter” or “judge” (from the root דין / din)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningInHebrew Context triple: [Dana, meaningInHebrew, “arbiter” or “judge” (from the root דין / din)]
-
A.
hebrewMeaning
chosen
Indicates that one entity specifies or provides the meaning or translation of another entity in the Hebrew language.
-
B.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
-
C.
meaningInGerman
Indicates that one entity expresses the meaning or translation of another entity in the German language.
-
D.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
E.
meaningInGreek
Indicates that something is expressed, translated, or holds a particular meaning in the Greek 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_69c00879e8048190b690717d19c5bc03 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0575d4ed481908eddc88e9b90e22f |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f21fe08190995df3c5c05fb8ea |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:11 p.m.