Triple
T121501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semper Fidelis |
E2453
|
entity |
| Predicate | hasMoralConcept |
P531
|
FINISHED |
| Object | loyalty |
—
|
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: loyalty | Statement: [Semper Fidelis, hasMoralConcept, loyalty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralConcept Context triple: [Semper Fidelis, hasMoralConcept, loyalty]
-
A.
hasConcept
chosen
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
B.
ethicalDebate
Indicates a relationship where parties are engaged in discussing, questioning, or disputing the moral rightness or wrongness of actions, policies, or principles.
-
C.
hasEthicalTeaching
Indicates that one entity provides, promotes, or embodies instruction or guidance related to ethical principles, values, or moral conduct for another entity.
-
D.
hasSecularAspects
Indicates that something includes or exhibits non-religious, worldly, or secular characteristics or dimensions.
-
E.
hasConnotation
Indicates that one entity carries an implied or associated meaning, tone, or emotional nuance in relation to another entity.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a258fd278481908ad4498e03f38e2f |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25647fe6081908cb0405266d35ff5 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.