Triple
T1753436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Yorkshire |
E38497
|
entity |
| Predicate | hasLargestAreaOf |
P32773
|
FINISHED |
| Object | any ceremonial county in England |
—
|
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: any ceremonial county in England | Statement: [North Yorkshire, hasLargestAreaOf, any ceremonial county in England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLargestAreaOf Context triple: [North Yorkshire, hasLargestAreaOf, any ceremonial county in England]
-
A.
hasLargestContinuousLandAreaOn
Indicates that an entity possesses the greatest uninterrupted expanse of land on a specified geographic region or surface compared to all other entities.
-
B.
hasLargestCountryByArea
Indicates that, among a set of compared entities, the subject is associated with the country that has the greatest land area.
-
C.
isSmallestByAreaIn
Indicates that an entity has the smallest area among all comparable entities within a specified set, group, or context.
-
D.
largestInCountry
Indicates that an entity is the largest of its kind within the specified country.
-
E.
isLargestParkOf
Indicates that a park is the largest park within a specified area, region, or administrative entity.
- 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_69a8862bdb2081908aefe831c8aa8017 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba6a63f588190b53b39c6b97d74f4 |
completed | March 7, 2026, 4:16 a.m. |
| PD | Predicate disambiguation | batch_69aa61c7ef4c8190abec87c96a787d82 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aba6a4c84c8190b3ce0bf69c2b5f6d |
completed | March 7, 2026, 4:16 a.m. |
Created at: March 4, 2026, 7:31 p.m.