Triple
T19412060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis Joseph Sheeran |
E485609
|
entity |
| Predicate | genreOfWorkAboutSubject |
P110441
|
FINISHED |
| Object | non-fiction crime literature |
—
|
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: non-fiction crime literature | Statement: [Francis Joseph Sheeran, genreOfWorkAboutSubject, non-fiction crime literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfWorkAboutSubject Context triple: [Francis Joseph Sheeran, genreOfWorkAboutSubject, non-fiction crime literature]
-
A.
genreOfWorkAbout
Indicates that a work is about a particular genre, expressing that the work’s subject matter or focus concerns that genre.
-
B.
genreOfWorkDescribedIn
Indicates that a work is characterized as belonging to a particular genre as described in another resource or context.
-
C.
genreOfWorkContributedTo
Indicates that an entity contributed to a work belonging to a specified genre.
-
D.
genreOfWorkHeWrites
chosen
Indicates that a person is an author who writes works belonging to a particular genre.
-
E.
genreOfWorkPerformedIn
Indicates that a specified genre characterizes the type of work that is performed in a particular event, context, or setting.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af681288190ba2ec52d5adb6a22 |
completed | April 20, 2026, 1:32 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.