Triple
T21649539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wars with Aram-Damascus |
E534298
|
entity |
| Predicate | secondarySourcesLanguage |
P2925
|
FINISHED |
| Object | Akkadian |
—
|
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: Akkadian | Statement: [Wars with Aram-Damascus, secondarySourcesLanguage, Akkadian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondarySourcesLanguage Context triple: [Wars with Aram-Damascus, secondarySourcesLanguage, Akkadian]
-
A.
languageOfSources
chosen
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
B.
secondaryLanguageContext
Indicates that the associated information, interaction, or content occurs within or is tailored to a secondary (non-primary) language setting or usage context.
-
C.
primaryLanguageSide2
Indicates that the second entity in the relationship uses or is associated with the primary language specified.
-
D.
secondEditionLanguage
Indicates that a work’s second edition is written in or associated with a particular language.
-
E.
sourceLanguageMeaning
Indicates that one entity expresses the meaning or sense of another entity in a particular source language.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef59131c88819082df8e5b87f5954b |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:35 p.m.