Triple
T5130208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Monastery |
E115677
|
entity |
| Predicate | languageOfManuscripts |
P17914
|
FINISHED |
| Object | Coptic |
—
|
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: Coptic | Statement: [White Monastery, languageOfManuscripts, Coptic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfManuscripts Context triple: [White Monastery, languageOfManuscripts, Coptic]
-
A.
languageOfWritings
chosen
Indicates that a specified language is the one in which certain writings or written works are composed.
-
B.
languageOfBooks
Indicates the language in which the referenced books are written or published.
-
C.
languageOfHistoricalRecord
Indicates the language in which a given historical record is written or recorded.
-
D.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
-
E.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
- 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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:42 p.m.