Triple
T18600389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dead |
E454602
|
entity |
| Predicate | hasSymbolicMeaningInWork |
P107935
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dead, hasSymbolicMeaningInWork, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymbolicMeaningInWork Context triple: [Dead, hasSymbolicMeaningInWork, yes]
-
A.
hasParticularSignificanceFor
Indicates that something holds a special, notable, or contextually important relevance or impact for a particular entity or situation.
-
B.
symbolismIn
chosen
Indicates that one entity functions as a symbol or representation within the context, meaning, or interpretive framework of another entity.
-
C.
symbolismFocus
Indicates that the primary emphasis of a work, element, or representation is on its symbolic meaning rather than its literal or functional aspects.
-
D.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
E.
symbolInBook
Indicates a relationship where a particular symbol appears or is used within a specific book.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5475018548190a2f497081af7ce55 |
completed | April 19, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:45 a.m.