Triple
T22321722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cadogan Place |
E551802
|
entity |
| Predicate | propertyValueLevel |
P59739
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Cadogan Place, propertyValueLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: propertyValueLevel Context triple: [Cadogan Place, propertyValueLevel, high]
-
A.
policyLevel
Indicates the degree or tier of strictness, scope, or priority associated with a given policy.
-
B.
representedLevel
Indicates that one entity denotes or encodes the degree, intensity, or value (i.e., the level) of another entity or property.
-
C.
hasRatingLevel
chosen
Indicates that an entity is associated with a particular rating level or score category.
-
D.
representationLevel
Indicates the degree or layer at which something stands in for, models, or symbolizes something else (e.g., more concrete vs. more abstract representation).
-
E.
designationLevel
Indicates the specific rank, tier, or level assigned to an entity within a designation or classification system.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15764d3a48190af79ce4642b7f563 |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:42 p.m.