Triple
T4897353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Vanity of vanities; all is vanity" |
E109713
|
entity |
| Predicate | hebrewTerm |
P24083
|
FINISHED |
| Object | hevel |
—
|
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: hevel | Statement: ["Vanity of vanities; all is vanity", hebrewTerm, hevel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hebrewTerm Context triple: ["Vanity of vanities; all is vanity", hebrewTerm, hevel]
-
A.
openingWordsHebrew
Indicates that the specified words are the opening (initial) words of a text or passage in Hebrew.
-
B.
languageTerm
chosen
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
-
C.
hasNameInHebrew
Indicates that an entity is associated with a specific name expressed in the Hebrew language.
-
D.
notableHebrewTranslator
Indicates that one entity is recognized for having translated works into Hebrew or from Hebrew in a particularly significant or distinguished way.
-
E.
etymologyGloss
Indicates that a term’s meaning is explained by a brief gloss specifically describing its etymological origin or source.
- 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_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. |
Created at: March 20, 2026, 1:28 p.m.