Triple
T3604044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Académie de la Grande Chaumière |
E76326
|
entity |
| Predicate | teachingEmphasizes |
P45342
|
FINISHED |
| Object | observation from live model |
—
|
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: observation from live model | Statement: [Académie de la Grande Chaumière, teachingEmphasizes, observation from live model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachingEmphasizes Context triple: [Académie de la Grande Chaumière, teachingEmphasizes, observation from live model]
-
A.
coreTeaching
Indicates that an entity serves as a primary or foundational teaching or instructional activity for another entity.
-
B.
typeOfTeaching
Indicates the specific method or style of teaching used in an instructional context.
-
C.
notableTeaching
Indicates that one entity is recognized for having taught, instructed, or educated another entity in a notable or significant way.
-
D.
skillEmphasis
chosen
Indicates that a particular skill is given special focus, priority, or importance within a context such as a role, task, or curriculum.
-
E.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc1e07bc481908d9fce18d36d8e0d |
completed | March 8, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69adb83d8b1c8190b3bddbc5dc995a87 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:22 p.m.