Triple
T8987378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth |
E214701
|
entity |
| Predicate | indirectOriginLanguage |
P86181
|
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: [Beth, indirectOriginLanguage, Hebrew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: indirectOriginLanguage Context triple: [Beth, indirectOriginLanguage, Hebrew]
-
A.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
B.
originalTextLanguage
Indicates the language in which a text was originally written or created before any translation or adaptation.
-
C.
originalLanguageContext
Indicates the language in which something was first created or expressed, providing the original linguistic context for its content or meaning.
-
D.
languageTranslatedFrom
Indicates that a language is the source/original language from which content has been translated into another language.
-
E.
originalLanguageOfWholeWork
Indicates that a given language is the primary or original language in which an entire work (such as a book, film, or other complete creation) was first produced or expressed.
- F. None of above. chosen
Provenance (4 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_69ca839f76bc8190a4b7123cdd682199 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc67ef19108190ac518c4f744b6d60 |
completed | April 1, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69cc5edba0f88190b97401636a076d7a |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5febd0a08190b2de6fb422343001 |
completed | March 31, 2026, 11:59 p.m. |
Created at: March 30, 2026, 7:04 p.m.