Triple
T2283136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark the Evangelist |
E51324
|
entity |
| Predicate | languageAssociatedWith |
P20184
|
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: [Mark the Evangelist, languageAssociatedWith, Greek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAssociatedWith Context triple: [Mark the Evangelist, languageAssociatedWith, Greek]
-
A.
languageAssociation
chosen
Indicates an association or relationship between entities based on a language they use, represent, or are linked to.
-
B.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
C.
associatedLanguageScript
Indicates that there is a relationship between a language and the script or writing system used to represent it.
-
D.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
E.
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).
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc21d6d748190980128c1bc5b9621 |
completed | March 7, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69abbdbb9e4c819085fc588626ec7c09 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.