Triple
T10395791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suite from 'Tinker Tailor Soldier Spy' |
E245010
|
entity |
| Predicate | sourceNovelGenre |
P82069
|
FINISHED |
| Object | spy novel |
—
|
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: spy novel | Statement: [Suite from 'Tinker Tailor Soldier Spy', sourceNovelGenre, spy novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sourceNovelGenre Context triple: [Suite from 'Tinker Tailor Soldier Spy', sourceNovelGenre, spy novel]
-
A.
literaryGenreOfWork
Indicates that a work belongs to or is classified under a particular literary genre.
-
B.
literaryGenreOfSourceWork
chosen
Indicates that a work belongs to, or is characterized by, a particular literary genre.
-
C.
literarySeriesGenre
Indicates that a literary series belongs to or is categorized under a particular genre.
-
D.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
E.
publishedGenre
Indicates that an entity has been published in, or is associated with, a particular genre.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9cf79348190975d6c1791e3b621 |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:06 p.m.