Triple
T13589196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French preparatory classes |
E324646
|
entity |
| Predicate | literaryTrackExample |
P110183
|
FINISHED |
| Object | hypokhâgne |
—
|
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: hypokhâgne | Statement: [French preparatory classes, literaryTrackExample, hypokhâgne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryTrackExample Context triple: [French preparatory classes, literaryTrackExample, hypokhâgne]
-
A.
literaryScript
Indicates a relationship where an entity serves as the written text or script of a literary work, such as a play, film, or other narrative production.
-
B.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
C.
literaryUnit
Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
-
D.
literarySource
Indicates that one entity serves as the written or literary origin, reference, or basis for another entity.
-
E.
literaryCenter
Indicates that a location functions as a primary hub or focal point for literary activity, such as writing, publishing, or literary culture.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb055cc98819091fab597b69e5e3e |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf9f3bdc8190838539aaef1f422b |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:49 p.m.