Triple
T19699691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinai front |
E473055
|
entity |
| Predicate | languageOfMostSources |
P2925
|
FINISHED |
| Object | Hebrew |
—
|
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: Hebrew | Statement: [Sinai front, languageOfMostSources, Hebrew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfMostSources Context triple: [Sinai front, languageOfMostSources, Hebrew]
-
A.
languageOfSources
chosen
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
B.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
C.
dominantMediaLanguage
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
-
D.
shareMajorLanguage
Indicates that the entities have at least one primary or major language in common.
-
E.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642b426608190a46abec3652a6ca0 |
completed | April 20, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
Created at: April 10, 2026, 1:46 p.m.