Triple
T7290249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Cohort |
E163972
|
entity |
| Predicate | scripturalLanguageName |
P75413
|
FINISHED |
| Object | speira Italike (Greek) |
—
|
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: speira Italike (Greek) | Statement: [Italian Cohort, scripturalLanguageName, speira Italike (Greek)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scripturalLanguageName Context triple: [Italian Cohort, scripturalLanguageName, speira Italike (Greek)]
-
A.
scriptureLanguageRegister
Indicates the specific linguistic register or style in which a piece of scripture is expressed (e.g., formal, liturgical, vernacular).
-
B.
hasLanguageOfScripture
Indicates that an entity’s scriptural or sacred texts are written or expressed in a specified language.
-
C.
scripturalBookNamedAfter
Indicates that a scriptural book bears the name of a particular person, place, or entity.
-
D.
religiousTextLanguageOf
Indicates that a particular language is the language in which a given religious text is written or primarily expressed.
-
E.
scripturalCorpus
Indicates that one entity is a body of scriptural or sacred texts associated with, or serving as the canonical writings for, another entity.
- 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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb6d4e308190af6b8c237988d7d8 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e82b0f9881909d29c99af1ea0dbf |
completed | March 27, 2026, 8:27 p.m. |
Created at: March 27, 2026, 3 p.m.