Triple
T5152634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Culver Girls Academy |
E116231
|
entity |
| Predicate | isBoardingFor |
P16557
|
FINISHED |
| Object | high school students |
—
|
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: high school students | Statement: [Culver Girls Academy, isBoardingFor, high school students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBoardingFor Context triple: [Culver Girls Academy, isBoardingFor, high school students]
-
A.
hasBoardingType
Indicates the specific manner or method by which an entity is boarded or accessed (e.g., how passengers or items are taken on).
-
B.
hasBoardingAreaFor
Indicates that one entity provides or contains a designated area where passengers can board another entity (such as a vehicle or vessel).
-
C.
usedWhenOnBoard
Indicates that something is employed or utilized while a person or object is on board a vehicle, vessel, or similar conveyance.
-
D.
hasBoardingStudents
chosen
Indicates that an educational institution accommodates students who reside on campus as boarders.
-
E.
boarding
Indicates that one entity is getting onto or entering a vehicle, vessel, or similar conveyance associated with another entity.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c1354c81908176703b4853c1a4 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b0fbb88190851e2d7ae1bdcc09 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:44 p.m.