Triple
T9828492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Modern Languages and Literatures |
E238719
|
entity |
| Predicate | typicalLanguagesTaught |
P1253
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Department of Modern Languages and Literatures, typicalLanguagesTaught, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLanguagesTaught Context triple: [Department of Modern Languages and Literatures, typicalLanguagesTaught, French]
-
A.
languageOfTeachings
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
-
B.
taughtAsForeignLanguageIn
chosen
Indicates that a language is taught as a foreign (non-native) language within a particular educational context or institution.
-
C.
alsoUsesLanguageOfInstruction
Indicates that an entity, in addition to its primary language, uses the same language that is designated as the language of instruction in a given context.
-
D.
typicalLanguages
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
E.
areTaughtIn
Indicates that certain subjects, courses, or topics are instructed or delivered within specific locations, classes, or educational settings.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3268fcc8190b7a028f224512e5f |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.