Triple
T6156701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of Saints Sergius and Bacchus |
E137338
|
entity |
| Predicate | convertedToMosqueInCentury |
P69501
|
FINISHED |
| Object | 16th century |
—
|
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: 16th century | Statement: [Church of Saints Sergius and Bacchus, convertedToMosqueInCentury, 16th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: convertedToMosqueInCentury Context triple: [Church of Saints Sergius and Bacchus, convertedToMosqueInCentury, 16th century]
-
A.
reconvertedToMosqueBy
Indicates that a building or site, previously used for another purpose, was changed back into a mosque by a specific agent or authority.
-
B.
convertedToIslamWith
Indicates that one entity adopted Islam through the influence, guidance, or involvement of another entity.
-
C.
hasMosque
Indicates that one entity possesses, contains, or is the location of a mosque.
-
D.
hasNumberOfMosques
Indicates the quantity of mosques associated with a given entity.
-
E.
usePeriodAsMosque
Indicates that a particular time period is utilized or designated for functioning as a mosque or for mosque-related activities.
- F. None of above. chosen
Provenance (4 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_69c008a45d008190832a9e19f5d63406 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d0376408190a2233375f478377e |
completed | March 22, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69c055f39e0881909ae56444b1b48929 |
completed | March 22, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69c056c87340819088003f427706ebf8 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:17 p.m.