Triple
T2944596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catholic schools |
E79468
|
entity |
| Predicate | mayServe |
P44125
|
FINISHED |
| Object | both Catholic and non-Catholic students |
—
|
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: both Catholic and non-Catholic students | Statement: [Catholic schools, mayServe, both Catholic and non-Catholic students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayServe Context triple: [Catholic schools, mayServe, both Catholic and non-Catholic students]
-
A.
mayServeOn
Indicates that one entity is permitted or eligible to serve on another entity, such as a group, body, or committee.
-
B.
canServeOn
Indicates that one entity is eligible or permitted to serve on another entity, such as a group, body, or committee.
-
C.
canServeIn
Indicates that one entity is eligible, authorized, or suitable to perform a role, function, or duty within another entity, context, or organization.
-
D.
mayHost
Indicates that an entity is permitted or able to serve as the location or organizer for another entity or event.
-
E.
isServed
Indicates that one entity provides or delivers a service, product, or assistance to another entity.
- 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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98b0db5081908e84def20a5e4a2d |
completed | March 8, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69ad96088fb481909976b436c2b729d9 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f520208190a4dc43372004555f |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:56 p.m.