Triple
T24983763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English College, Reims |
E625244
|
entity |
| Predicate | languageOfStudents |
P56
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [English College, Reims, languageOfStudents, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfStudents Context triple: [English College, Reims, languageOfStudents, English]
-
A.
languageOfSubjects
Indicates the language used by or associated with the subjects in question.
-
B.
languageOfTeachings
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
-
C.
languageBranchStudied
Indicates that a person studies or has studied a particular branch or subgroup of a language.
-
D.
primaryLanguageOfInstruction
chosen
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
E.
hasLanguageOfStudy
Indicates that an entity studies or is engaged in learning a particular language.
- 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_69e2ff254570819093d197b1900305ac |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 18, 2026, 6:02 a.m.