Triple
T5078768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jesus College Chapel |
E114461
|
entity |
| Predicate | hasChaplain |
P61290
|
FINISHED |
| Object | chaplain of Jesus College, Cambridge |
—
|
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: chaplain of Jesus College, Cambridge | Statement: [Jesus College Chapel, hasChaplain, chaplain of Jesus College, Cambridge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChaplain Context triple: [Jesus College Chapel, hasChaplain, chaplain of Jesus College, Cambridge]
-
A.
hasClergy
Indicates that an organization or institution possesses or is served by members of the clergy.
-
B.
hasChapels
Indicates that one entity contains, includes, or is associated with one or more chapels.
-
C.
hasChurch
Indicates that a place or entity possesses, contains, or is associated with a church.
-
D.
hasClergyType
Indicates the specific category or role of clergy associated with an entity.
-
E.
clergyCan
Indicates that members of the clergy are permitted or authorized to perform a specified action or exercise a particular role or function.
- 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_69bd443dbf908190a9401e9c2dc7bd7d |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74f75cf0819088be9e076eaf3168 |
completed | March 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69bd7157fe608190b4515d56fdd0a616 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd73d90b608190bd6c2407e84e2b64 |
completed | March 20, 2026, 4:20 p.m. |
Created at: March 20, 2026, 1:39 p.m.