Triple
T30633671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Night on the Galactic Railroad |
E779775
|
entity |
| Predicate | containsSymbolismOf |
P103297
|
FINISHED |
| Object | constellations |
—
|
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: constellations | Statement: [Night on the Galactic Railroad, containsSymbolismOf, constellations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsSymbolismOf Context triple: [Night on the Galactic Railroad, containsSymbolismOf, constellations]
-
A.
symbolismIn
Indicates that one entity functions as a symbol or representation within the context, meaning, or interpretive framework of another entity.
-
B.
incorporatesSymbolismFrom
chosen
Indicates that one entity includes or integrates symbolic elements, motifs, or meanings derived from another entity.
-
C.
languageOfSymbolism
Indicates that one entity is the language in which the symbolic meaning or symbolism of another entity is expressed or encoded.
-
D.
symbolismFocus
Indicates that the primary emphasis of a work, element, or representation is on its symbolic meaning rather than its literal or functional aspects.
-
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_69f224a431548190a44ad9d088dbf91f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ff234f32888190a1d800a3bda432eb |
completed | May 9, 2026, 12:06 p.m. |
| PD | Predicate disambiguation | batch_69ff228ae9a0819083f4b97c10b923f4 |
completed | May 9, 2026, 12:03 p.m. |
Created at: April 29, 2026, 8:28 p.m.