Triple
T33713158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ski municipality |
E863795
|
entity |
| Predicate | hadEducationalInstitution |
P113
|
FINISHED |
| Object | upper secondary schools |
—
|
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: upper secondary schools | Statement: [Ski municipality, hadEducationalInstitution, upper secondary schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadEducationalInstitution Context triple: [Ski municipality, hadEducationalInstitution, upper secondary schools]
-
A.
formerlyHadEducationalInstitution
Indicates that an entity once hosted or contained a particular educational institution, but that institution is no longer present or active there.
-
B.
educationalInstitutionServed
Indicates that one entity provides services, support, or resources to a particular educational institution.
-
C.
schoolAttended
Indicates that one entity has attended, or been enrolled as a student at, the school represented by the other entity.
-
D.
schoolTypeAttended
Indicates the specific type or category of school that an entity has attended.
-
E.
hasSchool
chosen
Indicates that an entity possesses, is associated with, or is served by a particular school.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fabe07848190bd4f14ac6dfa35b6 |
completed | May 3, 2026, 7:35 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:43 a.m.