Triple
T22539353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naunet |
E557242
|
entity |
| Predicate | pairedConcept |
P57196
|
FINISHED |
| Object | Nun as male water principle |
—
|
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: Nun as male water principle | Statement: [Naunet, pairedConcept, Nun as male water principle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pairedConcept Context triple: [Naunet, pairedConcept, Nun as male water principle]
-
A.
pairedThematicallyWith
Indicates a relationship where two entities are intentionally associated because they share a common theme, concept, or motif.
-
B.
pairedField
Indicates that one field is logically linked or associated with another field as a corresponding pair.
-
C.
hasConceptualOpposite
Indicates that one entity represents a concept that is fundamentally opposed or contrary in meaning to the concept represented by another entity.
-
D.
pairedSingleWith
Indicates that one entity is matched or associated as a single counterpart with another single entity, typically forming an exclusive one-to-one pairing.
-
E.
hasConceptualParallel
chosen
Indicates that one entity corresponds to or mirrors another at a conceptual level, showing a similar idea, structure, or pattern despite possible differences in form or 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f302cd4819098c97ca4fa96363e |
completed | April 29, 2026, 1:30 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:51 p.m.