Triple
T9401444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aesernia |
E226480
|
entity |
| Predicate | laterLanguageInUse |
P35092
|
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: [Aesernia, laterLanguageInUse, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterLanguageInUse Context triple: [Aesernia, laterLanguageInUse, Latin]
-
A.
laterLanguageDominant
Indicates that one language becomes the dominant or primary language for an entity at a later point in time, after another language previously held that role.
-
B.
laterSecondaryLanguageOfAdministration
Indicates that one language served as a subsequent or later secondary language used for administrative purposes in relation to another language.
-
C.
languageIntroduced
chosen
Indicates that a particular language was brought into use or made known within a certain context, time, or place.
-
D.
adoptedLanguage
Indicates that an entity has chosen and begun using a particular language, typically as its official, primary, or preferred means of communication.
-
E.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
- 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5157d66c819094c18f680c7093f7 |
completed | April 1, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69cca545b2448190a4297312e39c21ac |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:46 p.m.