Triple
T25005436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Technical Boy |
E625827
|
entity |
| Predicate | workOfFictionSubgenre |
P116833
|
FINISHED |
| Object | urban fantasy |
—
|
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: urban fantasy | Statement: [Technical Boy, workOfFictionSubgenre, urban fantasy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workOfFictionSubgenre Context triple: [Technical Boy, workOfFictionSubgenre, urban fantasy]
-
A.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
B.
literaryGenreOfWork
Indicates that a work belongs to or is classified under a particular literary genre.
-
C.
hasGenreInFiction
chosen
Indicates that a work of fiction belongs to or is categorized under a specific literary genre.
-
D.
literaryGenreOfSourceWork
Indicates that a work belongs to, or is characterized by, a particular literary genre.
-
E.
literaryGenreOfWorkAppearedIn
Indicates the literary genre of the work in which a given entity (such as a text, character, or element) appears.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44b1002e08190a764c1b557d39c23 |
completed | May 1, 2026, 6:41 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:05 a.m.