Triple
T12263182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thursday |
E292276
|
entity |
| Predicate | correspondsToLatinName |
P60629
|
FINISHED |
| Object | dies Iovis |
—
|
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: dies Iovis | Statement: [Thursday, correspondsToLatinName, dies Iovis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToLatinName Context triple: [Thursday, correspondsToLatinName, dies Iovis]
-
A.
hasLatinName
Indicates that an entity is associated with a specific Latin (scientific) name.
-
B.
correspondsToLatinWord
chosen
Indicates that one element is the equivalent or matching term of another element in Latin.
-
C.
hasLatinizedName
Indicates that an entity is associated with a version of its name that has been converted into Latin form or spelling.
-
D.
hasOfficialNameInLatin
Indicates that an entity has an official or formally recognized name expressed in the Latin language.
-
E.
correspondsToLatinLetter
Indicates that one entity is the counterpart or representation of another entity as a specific letter in the Latin alphabet.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.