Triple
T736108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Serbian Grammar School in Šabac |
E14935
|
entity |
| Predicate | typeOfSchool |
P303
|
FINISHED |
| Object | royal state school |
—
|
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: royal state school | Statement: [Royal Serbian Grammar School in Šabac, typeOfSchool, royal state school]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSchool Context triple: [Royal Serbian Grammar School in Šabac, typeOfSchool, royal state school]
-
A.
schoolSystemType
Indicates the classification or organizational model of a school system (e.g., public, private, charter, or other structural type).
-
B.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
C.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
E.
mediumOfInstruction
Indicates that a particular language or medium is used as the primary means of instruction or teaching in an educational context.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fafee081909bf356854c09aaff |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.