Triple
T10259379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France, Italy, Japan and the United Kingdom |
E240554
|
entity |
| Predicate | applicantIn |
P93110
|
FINISHED |
| Object | S.S. Wimbledon case |
—
|
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: S.S. Wimbledon case | Statement: [France, Italy, Japan and the United Kingdom, applicantIn, S.S. Wimbledon case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: applicantIn Context triple: [France, Italy, Japan and the United Kingdom, applicantIn, S.S. Wimbledon case]
-
A.
applicantType
Indicates the classification or category of an applicant in relation to an application or selection process.
-
B.
applicantState
Indicates the current status or condition assigned to an applicant within a process or system.
-
C.
applicationProcessIncludes
Indicates that an application process contains or encompasses a specific step, component, or sub-process as part of its overall workflow.
-
D.
appliedFor
Indicates that an entity has submitted a request or application to another entity for a position, service, benefit, or opportunity.
-
E.
applicantStates
Indicates that an applicant explicitly declares or asserts a particular fact, condition, or piece of information.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b5853081909cd0397e08a0f44d |
completed | April 7, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69d4d1edae6881909a65201b8e51ea0a |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d2b4ae548190b4a4c671f86b82d1 |
completed | April 7, 2026, 9:47 a.m. |
Created at: April 6, 2026, 11:32 a.m.