Triple
T7630488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Mark's School of Texas |
E172747
|
entity |
| Predicate | hasUpperSchool |
P78216
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [St. Mark's School of Texas, hasUpperSchool, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUpperSchool Context triple: [St. Mark's School of Texas, hasUpperSchool, yes]
-
A.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
-
B.
hasSchoolsAccess
Indicates that one entity has permission or the ability to access schools or school-related resources associated with another entity.
-
C.
hasHigherEducationAccess
Indicates that one entity has access to higher education opportunities or institutions relative to another entity or context.
-
D.
hasSchoolCategory
Indicates that an entity (such as a school or educational institution) is associated with a particular category or type of school.
-
E.
hasBoardingSchool
Indicates that an entity operates, contains, or is associated with a boarding school where students both study and reside.
- 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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6fe7323b0819081664662d2f26937 |
completed | March 27, 2026, 10:02 p.m. |
Created at: March 27, 2026, 3:56 p.m.