Triple
T8313707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rubicon River |
E194651
|
entity |
| Predicate | languageOfPhrase |
P8513
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [Rubicon River, languageOfPhrase, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfPhrase Context triple: [Rubicon River, languageOfPhrase, Latin]
-
A.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
B.
isLinguaFrancaOf
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
-
C.
otherLanguage
Indicates that an entity has or uses an additional language distinct from its primary or main language.
-
D.
languageOfExpression
chosen
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
E.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or 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_69ca82e6e2648190a31eaf6f4f757b2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f52c5cc8190b5a95ee0aa4ddda5 |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bf689c8190a9d9b6b872abf53d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:55 p.m.