Triple
T4771041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auto-Emancipation |
E105926
|
entity |
| Predicate | languageOfAvailableTranslations |
P52478
|
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: [Auto-Emancipation, languageOfAvailableTranslations, Hebrew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfAvailableTranslations Context triple: [Auto-Emancipation, languageOfAvailableTranslations, Hebrew]
-
A.
languageOfTranslations
chosen
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
-
B.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
C.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
D.
languageOfRecords
Indicates the language in which the records are written or maintained.
-
E.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd655e5dcc8190a932be9b1baaffb2 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.