Triple
T18658901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabarchini community |
E456137
|
entity |
| Predicate | usesInEducation |
P45097
|
FINISHED |
| Object | Italian language |
—
|
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: Italian language | Statement: [Tabarchini community, usesInEducation, Italian language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesInEducation Context triple: [Tabarchini community, usesInEducation, Italian language]
-
A.
usedInEducationIn
Indicates that something is employed or applied within educational contexts in a particular place or institution.
-
B.
usesInTeaching
Indicates that an agent employs a particular resource, method, or material as part of their teaching activities.
-
C.
educationUse
chosen
Indicates the use or application of something specifically for educational purposes or in an educational context.
-
D.
hasEducationalUse
Indicates that something is intended to be used for educational or instructional purposes.
-
E.
usesStudentsFor
Indicates that one entity employs or exploits students as a resource or means to carry out its activities or achieve its objectives.
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55087ae8081909cb4c0ce6c809d55 |
completed | April 19, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69e478d85864819093cbad5ed9b54878 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:48 a.m.