Triple
T14566607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | co-translating The Philokalia into English |
E341800
|
entity |
| Predicate | hasLanguageSource |
P9278
|
FINISHED |
| Object | 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: Greek | Statement: [co-translating The Philokalia into English, hasLanguageSource, Greek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageSource Context triple: [co-translating The Philokalia into English, hasLanguageSource, Greek]
-
A.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
B.
hasLanguageRepresentation
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
-
C.
hasLinguisticClassificationSource
Indicates the source or reference from which a linguistic classification has been derived or documented.
-
D.
hasLanguageOn
chosen
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
E.
hasLexiconSource
Indicates that a lexical item or entry is derived from, documented in, or otherwise sourced from a particular lexicon or lexical 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb38c6350819091090ffd15772f6f |
completed | April 14, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69de5c57489c8190b57917be1dba6ae6 |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:23 a.m.