Triple
T25268795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bensalem |
E633505
|
entity |
| Predicate | hasMoralFeature |
P47751
|
FINISHED |
| Object | emphasis on truthfulness |
—
|
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: emphasis on truthfulness | Statement: [Bensalem, hasMoralFeature, emphasis on truthfulness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralFeature Context triple: [Bensalem, hasMoralFeature, emphasis on truthfulness]
-
A.
hasMoralCharacteristic
chosen
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
-
B.
hasMoralArchetype
Indicates that an entity exemplifies or is characterized by a particular moral pattern, role, or ethical archetype.
-
C.
hasMoralComplexity
Indicates that the relationship or action involves nuanced ethical considerations, conflicting values, or ambiguity in determining what is morally right or wrong.
-
D.
hasMoralCode
Indicates that an entity adheres to or is guided by a set of moral principles or ethical rules.
-
E.
hasMoralPerspective
Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
- 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_69e75a92f48881909974ff9c11150a2e |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 21, 2026, 1:16 p.m.