Triple
T33974908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RHINE |
E871107
|
entity |
| Predicate | hasAllocation |
P194325
|
FINISHED |
| Object | randomized |
—
|
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: randomized | Statement: [RHINE, hasAllocation, randomized]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAllocation Context triple: [RHINE, hasAllocation, randomized]
-
A.
hasAllocatedTime
Indicates that a specific amount or period of time has been reserved or assigned for a particular entity, task, or activity.
-
B.
hasAllotments
Indicates that one entity has been assigned or granted specific portions, shares, or allocations of something (such as resources, land, or tasks).
-
C.
allocates
Indicates the act of assigning or distributing resources, responsibilities, or portions of something to specific entities or purposes.
-
D.
hasAllotmentArea
Indicates that an entity is associated with a specific area of land that has been formally allotted or assigned to it.
-
E.
usesAllocationTableType
Indicates that one entity employs or relies on a specific type of allocation table to organize or manage resource assignments.
- 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_69f3499da0188190ab1a4ff06fb06a2a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd6a1c1c4881908090053bc359b181 |
completed | May 8, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69fd696f24d8819091033afacbdaadc5 |
completed | May 8, 2026, 4:41 a.m. |
| PDg | Predicate description generation | batch_69fd6a1a38f081908c573aee4696de4f |
completed | May 8, 2026, 4:44 a.m. |
Created at: May 1, 2026, 1:50 a.m.