Triple
T28142869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madhavi Rao |
E714395
|
entity |
| Predicate | genreOfWorkDescribingSubject |
P102250
|
FINISHED |
| Object | true-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: true-crime literature | Statement: [Madhavi Rao, genreOfWorkDescribingSubject, true-crime literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfWorkDescribingSubject Context triple: [Madhavi Rao, genreOfWorkDescribingSubject, true-crime literature]
-
A.
genreOfWorkDescribedIn
Indicates that a work is characterized as belonging to a particular genre as described in another resource or context.
-
B.
genreOfWorkAbout
chosen
Indicates that a work is about a particular genre, expressing that the work’s subject matter or focus concerns that genre.
-
C.
genreOfWorkPerformedIn
Indicates that a specified genre characterizes the type of work that is performed in a particular event, context, or setting.
-
D.
genreOfWorkContributedTo
Indicates that an entity contributed to a work belonging to a specified genre.
-
E.
genreOfWorkDepictedIn
Indicates that a work depicts or represents another work belonging to 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_69efd6af156c81908f50c2cd7db0e1ef |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 27, 2026, 9:54 p.m.