Triple
T400027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Presbyterian |
E9258
|
entity |
| Predicate | derivesFromLanguage |
P1754
|
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: [Presbyterian, derivesFromLanguage, Greek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: derivesFromLanguage Context triple: [Presbyterian, derivesFromLanguage, Greek]
-
A.
hasLanguageOfOrigin
chosen
Indicates that one entity has its origin or source in the language specified by another entity.
-
B.
derivedFrom
Indicates that one entity originates, is obtained, or is developed from another source entity.
-
C.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
D.
recognizedAsDistinctLanguageFrom
Indicates that one language is formally acknowledged or treated as a separate and distinct language from another, rather than as a dialect or variant of it.
-
E.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec8e655c819081eff85c0ef55fa5 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96d17d08190878d3a68b17d51ca |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.