Triple
T33315890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crespi Carmelite High School |
E853013
|
entity |
| Predicate | hasUniformOrDressCode |
P2738
|
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: [Crespi Carmelite High School, hasUniformOrDressCode, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUniformOrDressCode Context triple: [Crespi Carmelite High School, hasUniformOrDressCode, yes]
-
A.
hasDressCode
chosen
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
-
B.
mayWearUniform
Indicates that an entity is permitted or authorized to wear a particular uniform in a given context.
-
C.
hasSchoolUniform
Indicates that an entity is required to wear or is associated with a specific school uniform as part of its affiliation with a school.
-
D.
woreUniformOf
Indicates that one entity was dressed in or used the official uniform associated with another entity (such as an organization, group, or role).
-
E.
wearsOnUniform
Indicates that an item is part of and is worn as a component of a uniform.
- 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_69f349685f088190b8fda44083a018a9 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: May 1, 2026, 1:33 a.m.