Triple
T11847896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Specialized High Schools Admissions Test |
E281826
|
entity |
| Predicate | preparationIndustry |
P101834
|
FINISHED |
| Object | test preparation courses |
—
|
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: test preparation courses | Statement: [Specialized High Schools Admissions Test, preparationIndustry, test preparation courses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preparationIndustry Context triple: [Specialized High Schools Admissions Test, preparationIndustry, test preparation courses]
-
A.
preparationBy
Indicates that one entity is created, assembled, or made ready through the actions or processes performed by another entity.
-
B.
sectorPreparation
Indicates that an entity is involved in getting a specific sector ready for operation, use, or transition through planning, setup, or related preparatory actions.
-
C.
preparationInvolved
Indicates that a particular preparation, process, or setup is involved in enabling or carrying out an action, event, or relationship.
-
D.
industrialCategory
Indicates the industry or sector classification to which an entity (such as a business or organization) belongs.
-
E.
operatorIndustry
Indicates that an operator (such as a company or organization) is engaged in or associated with a particular industry sector.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65c72088190b8de9550c455b788 |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:43 p.m.