Triple
T17610730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IB learner profile |
E428957
|
entity |
| Predicate | hasNumberOfAttributes |
P111144
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [IB learner profile, hasNumberOfAttributes, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfAttributes Context triple: [IB learner profile, hasNumberOfAttributes, 10]
-
A.
numberOfAttributes
chosen
Indicates the total count of distinct attributes or properties associated with a given entity or object.
-
B.
hasNumberOfFields
Indicates the specific count of fields or distinct data elements that an entity possesses.
-
C.
hasNumberOfObjects
Indicates that an entity is associated with a specific count or quantity of objects.
-
D.
hasSignificantAttribute
Indicates that an entity possesses an attribute that is especially important, influential, or noteworthy in the context of the relationship.
-
E.
hasNumberOfTypes
Indicates that an entity is associated with a specific count of distinct types or categories it possesses or includes.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2d294881908380b2ab0b4d2503 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:51 a.m.