Triple
T11060372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Abgar V of Osroene |
E261490
|
entity |
| Predicate | sourceLanguageOfTradition |
P1754
|
FINISHED |
| Object | Syriac texts |
—
|
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: Syriac texts | Statement: [King Abgar V of Osroene, sourceLanguageOfTradition, Syriac texts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sourceLanguageOfTradition Context triple: [King Abgar V of Osroene, sourceLanguageOfTradition, Syriac texts]
-
A.
hasSourceTradition
Indicates that something originates from, or is derived within, a particular cultural, religious, intellectual, or historical tradition.
-
B.
hasLanguageOfOrigin
chosen
Indicates that one entity has its origin or source in the language specified by another entity.
-
C.
governingLanguageTradition
Indicates that one language tradition holds authoritative or regulatory influence over another in terms of norms, standards, or accepted practices.
-
D.
primaryLanguageOfDesignTradition
Indicates the main natural language used within a particular design tradition for its communication, documentation, and conceptual development.
-
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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798e991848190b07c2f48dae38681 |
completed | April 9, 2026, 12:17 p.m. |
| PD | Predicate disambiguation | batch_69d74411d9e881908c0eeafa0f38e4b6 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:26 p.m.