Triple
T4897354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Vanity of vanities; all is vanity" |
E109713
|
entity |
| Predicate | hebrewMeaning |
P60525
|
FINISHED |
| Object | breath |
—
|
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: breath | Statement: ["Vanity of vanities; all is vanity", hebrewMeaning, breath]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hebrewMeaning Context triple: ["Vanity of vanities; all is vanity", hebrewMeaning, breath]
-
A.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
-
B.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
C.
latinMeaning
Indicates that one entity expresses or specifies the meaning or translation of another entity in Latin.
-
D.
nameMeaningLanguage
Indicates that a specified meaning of a name is expressed or interpreted in a particular language.
-
E.
openingWordsHebrew
Indicates that the specified words are the opening (initial) words of a text or passage in Hebrew.
- F. None of above. chosen
Provenance (4 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd7060f9988190afdf98eb0a38515d |
completed | March 20, 2026, 4:05 p.m. |
Created at: March 20, 2026, 1:28 p.m.