Triple
T15405604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jackson STEM Dual Language Magnet Academy |
E368444
|
entity |
| Predicate | languageModel |
P118669
|
FINISHED |
| Object | bilingual education |
—
|
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: bilingual education | Statement: [Jackson STEM Dual Language Magnet Academy, languageModel, bilingual education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageModel Context triple: [Jackson STEM Dual Language Magnet Academy, languageModel, bilingual education]
-
A.
coPilotWith
Indicates that two entities jointly serve as pilots or share piloting responsibilities for the same vehicle or mission.
-
B.
writingModel
Indicates that one entity serves as the writing system, script, or notation model used to represent the language or written content of another entity.
-
C.
aiCharacter
Indicates that an entity is a character or agent whose behavior or role is driven by artificial intelligence.
-
D.
writingTool
Indicates that one entity serves as a tool or instrument used by another entity for the act of writing.
-
E.
languageConsultant
Indicates that one entity serves as a language consultant, providing expert advice or guidance on language-related matters to another entity.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8fde64819082ec0c68df305561 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:20 a.m.