Triple
T31450741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andemta commentaries |
E802313
|
entity |
| Predicate | alsoTransmittedInLanguage |
P54680
|
FINISHED |
| Object | Amharic |
—
|
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: Amharic | Statement: [Andemta commentaries, alsoTransmittedInLanguage, Amharic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoTransmittedInLanguage Context triple: [Andemta commentaries, alsoTransmittedInLanguage, Amharic]
-
A.
languageOfTransmission
chosen
Indicates the language used to convey or transmit the content or information in a given communication or resource.
-
B.
laterLanguageOfDissemination
Indicates that one language was used to disseminate or publish a work at a later time than another language associated with the same work.
-
C.
alsoTranslatedAs
Indicates that something has an alternative translation or rendering in another language or form.
-
D.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
E.
hasRelatedLanguage
Indicates that one language is related to another through shared linguistic origins, features, or classification.
- 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_69f348c678ac81908a2e950867619061 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:12 p.m.