Triple
T20424206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Allegory of Life and Death |
E500949
|
entity |
| Predicate | hasSymbolicContent |
P25306
|
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: [The Allegory of Life and Death, hasSymbolicContent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymbolicContent Context triple: [The Allegory of Life and Death, hasSymbolicContent, yes]
-
A.
hasSymbolicValue
chosen
Indicates that something holds meaning, significance, or representational value beyond its literal or practical function.
-
B.
containsSymbolicAct
Indicates that one entity includes or incorporates a symbolic action or gesture associated with another entity.
-
C.
hasSymbolicForm
Indicates that one entity serves as the symbolic representation or abstract form of another entity.
-
D.
hasSymbolicTitle
Indicates that an entity holds a title or designation that is primarily symbolic or honorary rather than functional or operational.
-
E.
hasSymbolicInterpretation
Indicates that one entity is understood or used as a symbolic representation or metaphorical stand-in for another entity or concept.
- 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_69e0b4aa68fc8190b1a14c55575ef04a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67ba6c9b48190b1e96d0ef07002ed |
completed | April 20, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69e5766df0008190a73c4f613c29678f |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:30 a.m.