Triple
T7750915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dara |
E175757
|
entity |
| Predicate | hasMeaningInHebrew |
P60525
|
FINISHED |
| Object | nugget of wisdom |
—
|
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: nugget of wisdom | Statement: [Dara, hasMeaningInHebrew, nugget of wisdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningInHebrew Context triple: [Dara, hasMeaningInHebrew, nugget of wisdom]
-
A.
hebrewMeaning
chosen
Indicates that one entity specifies or provides the meaning or translation of another entity in the Hebrew language.
-
B.
hasNameInHebrew
Indicates that an entity is associated with a specific name expressed in the Hebrew language.
-
C.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
-
D.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
E.
lettersMeaning
Indicates that a set of letters or characters represents, signifies, or conveys a particular meaning or message.
- 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_69c69960b3588190a53aa590d31d9544 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c705257ca08190a78c592a1e616da8 |
completed | March 27, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69c7016df2b08190b2330a2010691431 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:08 p.m.