Triple
T12765184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Those Who Give Less in Measure and Weight |
E305103
|
entity |
| Predicate | moralTeachingEmphasizes |
P25343
|
FINISHED |
| Object | accuracy in measurement |
—
|
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: accuracy in measurement | Statement: [Those Who Give Less in Measure and Weight, moralTeachingEmphasizes, accuracy in measurement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralTeachingEmphasizes Context triple: [Those Who Give Less in Measure and Weight, moralTeachingEmphasizes, accuracy in measurement]
-
A.
moralTheme
chosen
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
B.
moralConcept
Indicates that one entity represents or embodies a moral or ethical concept in relation to another.
-
C.
moralExpectation
Indicates that one entity is expected, by moral or ethical standards, to behave in a certain way toward another entity or in a given situation.
-
D.
moralAttitude
Indicates a subject’s evaluative stance or judgment about the moral rightness or wrongness of another entity, action, or situation.
-
E.
moralBelief
Indicates that an agent holds a normative judgment about what is right, wrong, good, or bad in a given 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df1ef148190af525532fcb0933b |
completed | April 10, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.