Triple
T25923015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Politician |
E653221
|
entity |
| Predicate | hasGenreOfStory |
P161456
|
FINISHED |
| Object | maritime disaster |
—
|
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: maritime disaster | Statement: [SS Politician, hasGenreOfStory, maritime disaster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreOfStory Context triple: [SS Politician, hasGenreOfStory, maritime disaster]
-
A.
hasGenreInFiction
Indicates that a work of fiction belongs to or is categorized under a specific literary genre.
-
B.
hasGenreInSeries
Indicates that a particular genre is associated with, or applies to, a work as it appears within a specific series.
-
C.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular genre.
-
D.
hasGenreFeature
Indicates that something possesses a characteristic, element, or trait associated with a particular genre.
-
E.
literaryGenreAssociated
chosen
Indicates that there is an association between an entity and a particular literary genre with which it is related or classified.
- 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_69e7ab3eb9b881909c1390690551f868 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 22, 2026, 8:35 a.m.