Triple
T28615316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Server and Client Access License |
E724259
|
entity |
| Predicate | hasCALType |
P191788
|
FINISHED |
| Object | User CAL |
—
|
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: User CAL | Statement: [Server and Client Access License, hasCALType, User CAL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCALType Context triple: [Server and Client Access License, hasCALType, User CAL]
-
A.
hasCapType
Indicates that an entity possesses or is characterized by a specific type of cap or cap-like feature.
-
B.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
C.
hasCapitalType
Indicates that a specified location’s capital is of a particular type (e.g., political, administrative, or economic capital).
-
D.
hasCalderaType
Indicates that a caldera is classified as being of a particular type based on its formation or characteristics.
-
E.
hasCabType
Indicates that an entity is associated with or characterized by a specific type or category of cab.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
| PDg | Predicate description generation | batch_69fcec5e560481909cd710b88897e833 |
completed | May 7, 2026, 7:47 p.m. |
Created at: April 28, 2026, 4:31 a.m.