Triple
T1450724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menaion |
E31283
|
entity |
| Predicate | languageOfEarlyManuscripts |
P3926
|
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: [Menaion, languageOfEarlyManuscripts, Greek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfEarlyManuscripts Context triple: [Menaion, languageOfEarlyManuscripts, Greek]
-
A.
earliestManuscripts
Indicates that the related entity (e.g., a text or work) is associated with its earliest known surviving manuscripts or documentary witnesses.
-
B.
ancientLanguages
Indicates that the related entities are languages that originated in and were used during ancient historical periods.
-
C.
languageOfEarliestForm
chosen
Indicates the language in which the earliest known form or attested version of something (e.g., a text, name, or expression) is recorded.
-
D.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
-
E.
earliestTextsIn
Indicates that certain texts are among the earliest known examples found in or associated with a particular place or context.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c57bc0908190a57e6bc3d20d5e3c |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47cdbd0819092022344a2f4ad7b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.