Triple
T14704569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rougon family |
E345392
|
entity |
| Predicate | appearsAcrossNumberOfNovels |
P115425
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Rougon family, appearsAcrossNumberOfNovels, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsAcrossNumberOfNovels Context triple: [Rougon family, appearsAcrossNumberOfNovels, 20]
-
A.
appearsInBookNumber
Indicates that an entity is featured or mentioned in a specific book identified by its number within a series or collection.
-
B.
novelAuthorOfAppearance
Indicates that a person is the author of a novel in which a given character or entity appears.
-
C.
associatedWithAuthorOfSourceNovel
Indicates a relationship where one entity is connected or linked in some way to the author of the original source novel.
-
D.
novelReleaseYear
Indicates the calendar year in which a novel was first released or published.
-
E.
lightNovelVolumesCount
Indicates the number of volumes that exist for a given light novel.
- F. None of above. chosen
Provenance (4 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb6086c608190a66c64e23a3e002f |
completed | April 14, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716d3aac8190aaa6dc1f099b86e8 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:28 a.m.