Triple
T15569916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colégio de Jesus (Coimbra) |
E374210
|
entity |
| Predicate | functionStartAsJesuitCollege |
P119226
|
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: [Colégio de Jesus (Coimbra), functionStartAsJesuitCollege, 16th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: functionStartAsJesuitCollege Context triple: [Colégio de Jesus (Coimbra), functionStartAsJesuitCollege, 16th century]
-
A.
isJesuitInstitution
Indicates that an institution is affiliated with, founded by, or operated under the auspices of the Jesuit (Society of Jesus) Catholic religious order.
-
B.
functionStartAsCathedral
Indicates that the function or use of an entity originally began as a cathedral.
-
C.
functionStartAsGovernmentColleges
Indicates that the entities began their existence or operation specifically as government-run colleges.
-
D.
officeStartForMinisterOfEducation
Indicates the date or point in time when a person begins serving as the Minister of Education.
-
E.
oldestJesuitCollegeIn
Indicates that the subject is the oldest Jesuit college located within the specified place or region.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e1de0488190b3639fc25f79d343 |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f05f708190850f1d8782e132b0 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:10 a.m.