Triple
T26822849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Undiplomatic Murder |
E675297
|
entity |
| Predicate | fictionalGenreCategory |
P69182
|
FINISHED |
| Object | American crime 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: American crime novel | Statement: [Undiplomatic Murder, fictionalGenreCategory, American crime novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalGenreCategory Context triple: [Undiplomatic Murder, fictionalGenreCategory, American crime novel]
-
A.
fictionalGenre
chosen
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
B.
fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other entity.
-
C.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
D.
hasGenreInFiction
Indicates that a work of fiction belongs to or is categorized under a specific literary genre.
-
E.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
- 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_69eee9b6b28481909332f83eb17e5170 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 27, 2026, 4:56 a.m.