Triple
T1292002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Benedict of Nursia |
E27566
|
entity |
| Predicate | ruleEmphasizes |
P17414
|
FINISHED |
| Object | prayer and work (ora et labora) |
—
|
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: prayer and work (ora et labora) | Statement: [Saint Benedict of Nursia, ruleEmphasizes, prayer and work (ora et labora)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruleEmphasizes Context triple: [Saint Benedict of Nursia, ruleEmphasizes, prayer and work (ora et labora)]
-
A.
hasEmphasis
chosen
Indicates that one element is given special stress, importance, or prominence relative to others.
-
B.
strategyEmphasis
Indicates an entity’s primary focus or priority within a broader strategy or plan.
-
C.
notableRule
Indicates that a rule or regulation is particularly significant, prominent, or noteworthy within a given context.
-
D.
styleOfRule
Indicates the stylistic or formatting convention that a particular rule follows or is expressed in.
-
E.
ruleOfLife
Indicates a guiding principle, norm, or code that governs how an entity should live or behave.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d7d15081909d3af19b9297f1cc |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.