Triple
T30689534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashworth |
E781282
|
entity |
| Predicate | hasFrequencyCategoryInEngland |
P28499
|
FINISHED |
| Object | uncommon |
—
|
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: uncommon | Statement: [Ashworth, hasFrequencyCategoryInEngland, uncommon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrequencyCategoryInEngland Context triple: [Ashworth, hasFrequencyCategoryInEngland, uncommon]
-
A.
hasFrequencyRankInEngland
Indicates that an entity (such as a name or term) has a specific position in a ranked list based on how frequently it occurs in England.
-
B.
hasFrequencyCategory
chosen
Indicates that something is associated with a particular classification of how often it occurs or is used.
-
C.
hasApproximateEuropeanFrequency
Indicates that the subject has an estimated or approximate occurrence rate within European populations.
-
D.
hasFrequencyCoverage
Indicates that one entity provides, supports, or is applicable across a specified range or set of frequencies associated with another entity.
-
E.
isLocatedInPartOfEngland
Indicates that one entity is geographically situated within a specific part or region of England.
- 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_69f224a92f54819095499b4d32bd5134 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 29, 2026, 8:33 p.m.