Triple
T4694119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orders, decorations, and medals of Portugal |
E104101
|
entity |
| Predicate | hasGradeSystem |
P58852
|
FINISHED |
| Object | multiple classes |
—
|
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: multiple classes | Statement: [Orders, decorations, and medals of Portugal, hasGradeSystem, multiple classes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGradeSystem Context triple: [Orders, decorations, and medals of Portugal, hasGradeSystem, multiple classes]
-
A.
hasGrades
Indicates that an entity possesses or is associated with one or more grade values, typically reflecting evaluations or scores.
-
B.
hasGradeCount
Indicates a relationship where an entity is associated with the number of grades it has or has received.
-
C.
hasAcademicSystem
Indicates that an entity is associated with or operates under a particular academic or educational system.
-
D.
gradingSystem
Indicates the method or criteria by which performance, quality, or achievement is evaluated and assigned a grade or score.
-
E.
usesAcademicCreditSystem
Indicates that an institution or program organizes and evaluates coursework using a formal academic credit system (e.g., credit hours or units).
- 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
| PDg | Predicate description generation | batch_69bd660414b08190ab37467755d383b5 |
completed | March 20, 2026, 3:21 p.m. |
Created at: March 20, 2026, 1:17 p.m.