Triple
T4992684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avgad |
E112168
|
entity |
| Predicate | hasConceptualDomain |
P531
|
FINISHED |
| Object | mystical exegesis of sacred texts |
—
|
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: mystical exegesis of sacred texts | Statement: [Avgad, hasConceptualDomain, mystical exegesis of sacred texts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConceptualDomain Context triple: [Avgad, hasConceptualDomain, mystical exegesis of sacred texts]
-
A.
hasConcept
chosen
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
B.
hasConceptualOrigin
Indicates that something conceptually originates from, is derived from, or is fundamentally based on another thing.
-
C.
hasConceptualBoundary
Indicates that one entity defines, marks, or establishes the abstract limit or scope of another entity’s meaning, applicability, or conceptual extent.
-
D.
hasSubConcept
Indicates that one concept is a more specific, subordinate, or narrower idea within the scope of another, more general concept.
-
E.
hasLinguisticDomain
Indicates that something (such as a term, expression, or resource) is associated with or applies within a particular linguistic domain or language context.
- 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_69bd441be7bc8190b530362d427b97d2 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74249a8c8190952680aee06a9286 |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd71492dec8190af4c27a3043b35cc |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.