Triple
T2150493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Engineering, Pontifical Xavierian University |
E47167
|
entity |
| Predicate | offersField |
P178
|
FINISHED |
| Object | various engineering disciplines |
—
|
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: various engineering disciplines | Statement: [Faculty of Engineering, Pontifical Xavierian University, offersField, various engineering disciplines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersField Context triple: [Faculty of Engineering, Pontifical Xavierian University, offersField, various engineering disciplines]
-
A.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
B.
offersEdition
Indicates that one entity provides or makes available a particular version or edition of another entity.
-
C.
offersServiceTo
Indicates that one entity provides or makes a service available for the benefit or use of another entity.
-
D.
offersProgram
chosen
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
E.
offersViewOf
Indicates that one entity provides a vantage point from which another entity can be seen or visually appreciated.
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe45dbf481909c0da056a1a99ece |
completed | March 7, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69abbd9a60648190b20b116be5c7ad98 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.