Triple
T17053361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Military Boekelo-Enschede |
E413755
|
entity |
| Predicate | hasDisciplineCode |
P121458
|
FINISHED |
| Object | eventing (EV) |
—
|
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: eventing (EV) | Statement: [Military Boekelo-Enschede, hasDisciplineCode, eventing (EV)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisciplineCode Context triple: [Military Boekelo-Enschede, hasDisciplineCode, eventing (EV)]
-
A.
disciplineCode
chosen
Indicates the specific field, subject area, or branch of study/classification to which an entity is assigned or categorized.
-
B.
hasDisciplineSystem
Indicates that an entity possesses or is governed by a particular system of rules, methods, or practices for maintaining discipline.
-
C.
hasDisplayDiscipline
Indicates that an entity is associated with a particular academic or professional discipline in which its content is displayed or categorized.
-
D.
hasDisciplineSections
Indicates that an entity is associated with one or more sections that belong to a particular discipline or field.
-
E.
hasAwardedDiscipline
Indicates that one entity has formally imposed or granted a disciplinary action or sanction upon another entity.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa491008190ad013ee37532aa51 |
completed | April 18, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.