Triple
T17805057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer of the Order of Orange-Nassau |
E444534
|
entity |
| Predicate | orderHasSixClasses |
P128986
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Officer of the Order of Orange-Nassau, orderHasSixClasses, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orderHasSixClasses Context triple: [Officer of the Order of Orange-Nassau, orderHasSixClasses, true]
-
A.
orderHasThreeGrades
Indicates that an order is associated with exactly three distinct grades or levels.
-
B.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
C.
orderClass
Indicates that one entity is classified into a particular order or category within a hierarchical or taxonomic system.
-
D.
hasMultipleCourses
Indicates that an entity is associated with more than one course within the given context.
-
E.
numberOfCourses
Indicates the quantity of courses associated with a given entity.
- F. None of above. chosen
Provenance (4 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4880385b48190b8dea0f05dfa1300 |
completed | April 19, 2026, 7:45 a.m. |
| PD | Predicate disambiguation | batch_69e3d8de28688190844b65acf6af54e6 |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:14 a.m.