Triple
T7927467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ap Rhys |
E184102
|
entity |
| Predicate | hasHistoricalUsageType |
P64171
|
FINISHED |
| Object | patronymic naming formula |
—
|
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: patronymic naming formula | Statement: [ap Rhys, hasHistoricalUsageType, patronymic naming formula]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalUsageType Context triple: [ap Rhys, hasHistoricalUsageType, patronymic naming formula]
-
A.
hasHistoricalUsageIn
chosen
Indicates that something has been used or practiced within a particular historical period, context, or tradition.
-
B.
hasHistoricalCategory
Indicates that something is associated with a particular historical classification, period, or type based on its past context or significance.
-
C.
hasTypeHistory
Indicates that an entity is associated with a record or sequence of its past and present types or classifications over time.
-
D.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
E.
hasHistoricResourceType
Indicates that an entity is associated with a particular category or type of historic resource.
- 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_69ca828fe7bc819090f52c88dcd72183 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aafdb5c8190b7f2ce5349305f78 |
completed | March 31, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69cae9316e98819080be7bf1a6ff92f1 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:07 p.m.