Triple
T12765176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Those Who Give Less in Measure and Weight |
E305103
|
entity |
| Predicate | moralLessonFor |
P57332
|
FINISHED |
| Object | Muslim traders |
—
|
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: Muslim traders | Statement: [Those Who Give Less in Measure and Weight, moralLessonFor, Muslim traders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralLessonFor Context triple: [Those Who Give Less in Measure and Weight, moralLessonFor, Muslim traders]
-
A.
moralOfMyth
Indicates the underlying lesson, ethical teaching, or message conveyed by a myth.
-
B.
moralTheme
Indicates that a work, event, or situation embodies or conveys a particular ethical lesson, value, or moral principle.
-
C.
hasMoralMessage
chosen
Indicates that something conveys or embodies a lesson, value, or guidance about what is right or wrong behavior.
-
D.
derivesMoralityFrom
Indicates that one entity bases or grounds its moral principles, judgments, or ethical framework on another entity.
-
E.
moralExemplarOf
Indicates that one entity serves as a model or standard of moral behavior for another entity or group.
- 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.