Triple
T358460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argosy |
E7596
|
entity |
| Predicate | convertedToAllFiction |
P5574
|
FINISHED |
| Object | 1894 |
—
|
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: 1894 | Statement: [Argosy, convertedToAllFiction, 1894]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: convertedToAllFiction Context triple: [Argosy, convertedToAllFiction, 1894]
-
A.
fictionalizationOf
Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
-
B.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
C.
fictionalUniverseCreated
Indicates that one entity is the creator or originator of a particular fictional universe or setting in which stories or works take place.
-
D.
convertedFrom
chosen
Indicates that one entity has been transformed or changed in form, type, or representation from another entity.
-
E.
originallyWrittenFor
Indicates that a work was initially created or composed with a particular recipient, medium, context, or purpose in mind.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebb0e348819086e3ccd96c7b129e |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e959ce948190a201c017eecb7c95 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.