Triple
T7347948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadaqah |
E169424
|
entity |
| Predicate | relatedToRootMeaning |
P37
|
FINISHED |
| Object | 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: truthfulness | Statement: [Sadaqah, relatedToRootMeaning, truthfulness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToRootMeaning Context triple: [Sadaqah, relatedToRootMeaning, truthfulness]
-
A.
semanticRootMeaning
Indicates the fundamental or core meaning that underlies a word, phrase, or expression in a semantic structure.
-
B.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
C.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
D.
definitionOfRelatedConcept
Indicates that one concept provides the formal meaning, explanation, or characterization of another closely related concept.
-
E.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
- 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_69c68a5878888190968ce4d04db8d69f |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f139505c8190a7158cf59a6e089e |
completed | March 27, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69c6f02aeeb8819099d1626566cec18b |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:05 p.m.