Triple
T9099319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Legrand |
E218110
|
entity |
| Predicate | workAppearedInGenre |
P21332
|
FINISHED |
| Object | Detective fiction precursor |
—
|
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: Detective fiction precursor | Statement: [William Legrand, workAppearedInGenre, Detective fiction precursor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workAppearedInGenre Context triple: [William Legrand, workAppearedInGenre, Detective fiction precursor]
-
A.
publishedGenre
Indicates that an entity has been published in, or is associated with, a particular genre.
-
B.
genreOfAppearance
chosen
Indicates the genre or type of creative work in which an entity appears.
-
C.
workedOnGenre
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
D.
seriesGenreOfNotableWork
Indicates that a particular genre characterizes the notable work associated with a series.
-
E.
coveredInGenre
Indicates that a work or item is associated with, categorized under, or treated within 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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9710ac04819096b9c8d3399b9c35 |
completed | April 1, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69cc65fc7f408190a5846e29ab3b97e5 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:15 p.m.