Triple
T7243764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beauty (essay) |
E156421
|
entity |
| Predicate | hasEthicalClaim |
P73574
|
FINISHED |
| Object | true beauty inspires virtue |
—
|
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: true beauty inspires virtue | Statement: [Beauty (essay), hasEthicalClaim, true beauty inspires virtue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthicalClaim Context triple: [Beauty (essay), hasEthicalClaim, true beauty inspires virtue]
-
A.
hasEthicalText
chosen
Indicates that an entity is associated with or contains text expressing ethical principles, guidelines, or considerations.
-
B.
hasEthicalDimension
Indicates that the relationship, action, or situation involves moral considerations, value judgments, or ethical implications.
-
C.
hasEthicalStandard
Indicates that an entity adheres to, follows, or is governed by a specified set of ethical principles or standards.
-
D.
hasEthicalConstraint
Indicates that an entity is subject to a specified ethical rule, limitation, or normative requirement that governs its behavior or decisions.
-
E.
hasEthicalAssessment
Indicates that an entity has been evaluated according to ethical criteria or standards.
- 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_69c68827b5e481908dc05e145b2c92d4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea58533481909af7a4a6ade40eff |
completed | March 27, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69c6e7644648819096a5e2de5d0dbe97 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.