Triple
T19293803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mother of Georgia |
E482507
|
entity |
| Predicate | leftHandSymbolism |
P77714
|
FINISHED |
| Object | offering wine to friends |
—
|
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: offering wine to friends | Statement: [Mother of Georgia, leftHandSymbolism, offering wine to friends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leftHandSymbolism Context triple: [Mother of Georgia, leftHandSymbolism, offering wine to friends]
-
A.
handMeaning
chosen
Indicates that one entity uses or positions its hand in a particular way to convey a specific meaning, message, or communicative intent toward another entity.
-
B.
handedness
Indicates the preference or dominance of one hand over the other in performing actions or tasks.
-
C.
carriedInRightOrLeftHand
Indicates that an entity is being held and transported either in the right hand or in the left hand of an agent.
-
D.
leftHandRuleUsedFor
Indicates that the left-hand rule is applied as a method or principle to analyze, determine, or relate certain physical quantities or directions in a given context.
-
E.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc824b448190865230eed8ef9ebf |
completed | April 20, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:31 p.m.