Triple
T5094315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catholic Homilies |
E114828
|
entity |
| Predicate | intendedClarity |
P20179
|
FINISHED |
| Object | to be easily understood by laypeople |
—
|
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: to be easily understood by laypeople | Statement: [Catholic Homilies, intendedClarity, to be easily understood by laypeople]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedClarity Context triple: [Catholic Homilies, intendedClarity, to be easily understood by laypeople]
-
A.
clarifiesThat
Indicates that one entity explains or makes another entity more understandable by removing ambiguity or confusion about it.
-
B.
languageAmbiguity
Indicates that the meaning, interpretation, or reference of a linguistic expression is unclear or can be understood in multiple ways.
-
C.
intendedMessage
Indicates that one entity is the message or content that another entity aims or plans to communicate.
-
D.
clarifiesStandard
Indicates that one entity explains, specifies, or makes more precise the meaning or application of a given standard for another entity.
-
E.
intendedReadingLevel
chosen
Indicates the reading proficiency or audience level that a text or resource is designed or meant to be understood by.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7563ad608190879a26a0bf07c3f6 |
completed | March 20, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69bd715c0a448190afc837c6c31dc6ab |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:40 p.m.