Triple
T5446384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carathéodory metric |
E122257
|
entity |
| Predicate | isLocalizable |
P64359
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Carathéodory metric, isLocalizable, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLocalizable Context triple: [Carathéodory metric, isLocalizable, false]
-
A.
supportsInternationalization
Indicates that an entity provides functionality or features that enable use across multiple languages, locales, or regional formats.
-
B.
locale
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
-
C.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
-
D.
hasLocalizedTimeRules
Indicates that an entity applies specific time-related rules or conventions that are tailored to a particular locale or region.
-
E.
localeType
Indicates the classification or category of a locale (such as region, city, or venue type) that characterizes the kind of place involved in the relationship.
- 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_69bd4640f52c81909e653ec361f66d76 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
| PDg | Predicate description generation | batch_69bd95bd53f48190a03144beb290f2cb |
completed | March 20, 2026, 6:45 p.m. |
Created at: March 20, 2026, 2:07 p.m.