Triple
T14096292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel bat Kalba Savua |
E339260
|
entity |
| Predicate | famousQuoteAboutHer |
P492
|
FINISHED |
| Object | “Sheli v’shelachem shelah hu” (Mine and yours are hers) – said by Rabbi Akiva |
—
|
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: “Sheli v’shelachem shelah hu” (Mine and yours are hers) – said by Rabbi Akiva | Statement: [Rachel bat Kalba Savua, famousQuoteAboutHer, “Sheli v’shelachem shelah hu” (Mine and yours are hers) – said by Rabbi Akiva]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: famousQuoteAboutHer Context triple: [Rachel bat Kalba Savua, famousQuoteAboutHer, “Sheli v’shelachem shelah hu” (Mine and yours are hers) – said by Rabbi Akiva]
-
A.
notableQuote
chosen
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
-
B.
quotationText
Indicates that the associated text is the exact content of a quotation made or referenced in the relationship.
-
C.
notableQuoteTranslation
Indicates that one quote is a translation of another quote, preserving its meaning across different languages.
-
D.
quoteLanguage
Indicates that a quoted text is expressed in a particular language.
-
E.
oftenMisquotedAs
Indicates that one entity is frequently incorrectly cited or repeated as being another specific entity or expression.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fb7fb3c819083266dbe7e93aaff |
completed | April 14, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.