Triple
T33488934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Jacques Rousseau: la transparence et l’obstacle |
E857687
|
entity |
| Predicate | analyzesGenre |
P176668
|
FINISHED |
| Object | autobiographical writing |
—
|
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: autobiographical writing | Statement: [Jean-Jacques Rousseau: la transparence et l’obstacle, analyzesGenre, autobiographical writing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: analyzesGenre Context triple: [Jean-Jacques Rousseau: la transparence et l’obstacle, analyzesGenre, autobiographical writing]
-
A.
genreFunction
Indicates the role or purpose that a genre serves in relation to an entity, such as how it functions within classification, interpretation, or use.
-
B.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
C.
genreWithin
Indicates that one genre is a subgenre or more specific category contained within another, broader genre.
-
D.
commonGenre
Indicates that two entities share at least one genre in common.
-
E.
namedForGenre
Indicates that something is given a name based on or derived from a particular genre.
- 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_69f3497547608190a1a0f2365fb713ee |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e564f2a08190bc99090d41429022 |
completed | May 3, 2026, 6:04 a.m. |
| PD | Predicate disambiguation | batch_69f6e3db74c081909a991309d835d477 |
completed | May 3, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69f6e4a260808190b4aca0b988f3e593 |
completed | May 3, 2026, 6:01 a.m. |
Created at: May 1, 2026, 1:38 a.m.