Triple
T31249754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan |
E796780
|
entity |
| Predicate | attributedQuote |
P21904
|
FINISHED |
| Object | "Nothing can hinder the Lord from saving, whether by many or by few" |
—
|
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: "Nothing can hinder the Lord from saving, whether by many or by few" | Statement: [Jonathan, attributedQuote, "Nothing can hinder the Lord from saving, whether by many or by few"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attributedQuote Context triple: [Jonathan, attributedQuote, "Nothing can hinder the Lord from saving, whether by many or by few"]
-
A.
quoteAttributedTo
chosen
Indicates that a specific quotation is credited as having been said or written by a particular source or entity.
-
B.
notableQuoteOrigin
Indicates that a quoted statement is originally attributed to a particular source or context.
-
C.
quoteType
Indicates the specific category or classification of a quotation, such as its style, purpose, or contextual role in discourse.
-
D.
quoteLanguage
Indicates that a quoted text is expressed in a particular language.
-
E.
quotationText
Indicates that the associated text is the exact content of a quotation made or referenced in the relationship.
- 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6a0ea04888190ac3a813b603bcb5c |
completed | May 3, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 29, 2026, 9:11 p.m.