Triple
T1251977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | École du Louvre |
E26894
|
entity |
| Predicate | offersContinuingEducation |
P25827
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [École du Louvre, offersContinuingEducation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersContinuingEducation Context triple: [École du Louvre, offersContinuingEducation, yes]
-
A.
offersCourseType
Indicates that an entity provides or makes available a course of a specified type.
-
B.
offersCurriculum
Indicates that one entity provides or makes available a specific curriculum to another entity.
-
C.
offersDegree
Indicates that an institution or program provides a specific academic degree as an available qualification.
-
D.
offersEducationMode
Indicates that an entity provides a particular mode or format in which education or instruction is delivered.
-
E.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf85e1e08190ba6aac3fcd8bb3e7 |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6c977c8190a2bf3e8b67a59beb |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:47 p.m.