Triple
T6466108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arab Christian community of Nazareth |
E142235
|
entity |
| Predicate | languageOfMedia |
P31857
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [Arab Christian community of Nazareth, languageOfMedia, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfMedia Context triple: [Arab Christian community of Nazareth, languageOfMedia, Arabic]
-
A.
dominantMediaLanguage
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
-
B.
languageSpokenOnScreen
Indicates that a particular language is used in spoken dialogue or audible communication within an on-screen work (such as a film, show, or video).
-
C.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
D.
contentLanguage
chosen
Indicates the language in which the content is expressed or intended to be understood.
-
E.
languageOfTransmission
Indicates the language used to convey or transmit the content or information in a given communication or resource.
- 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a1159ec81909bbfa9a9d6fa1616 |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:49 p.m.