Triple
T935224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zohar |
E20179
|
entity |
| Predicate | interpretationMethod |
P21759
|
FINISHED |
| Object | symbolic exegesis |
—
|
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: symbolic exegesis | Statement: [Zohar, interpretationMethod, symbolic exegesis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interpretationMethod Context triple: [Zohar, interpretationMethod, symbolic exegesis]
-
A.
interpretiveStatus
Indicates the evaluative or explanatory stance assigned to something, such as how it is understood, classified, or interpreted within a given context.
-
B.
isInterpretedBy
Indicates that something (such as data, a work, or a signal) is given meaning, understanding, or explanation by a particular agent or process.
-
C.
interpretedAs
Indicates that something is understood, perceived, or taken to mean something else, often based on context or subjective judgment.
-
D.
interpretedInCase
Indicates that something is understood, analyzed, or given meaning within the context of a particular case or specific situational scenario.
-
E.
decodingMethod
Indicates the technique or process used to convert encoded or encrypted data back into its original, interpretable form.
- F. None of above. chosen
Provenance (4 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b363ea5c819098ec1d87f785bad4 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29b245c8190b143f28b77fede3c |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.