Triple
T369735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pontifical Xavierian University |
E8240
|
entity |
| Predicate | hasResearchCentersIn |
P11730
|
FINISHED |
| Object | health sciences |
—
|
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: health sciences | Statement: [Pontifical Xavierian University, hasResearchCentersIn, health sciences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResearchCentersIn Context triple: [Pontifical Xavierian University, hasResearchCentersIn, health sciences]
-
A.
containsResearchStation
Indicates that one entity geographically includes or hosts a research station within its boundaries.
-
B.
isIndustrialCenter
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
-
C.
hasHeadquartersType
Indicates the specific kind or classification of headquarters associated with an entity.
-
D.
isEducationalCenterOf
Indicates that an institution functions as the primary educational center serving, representing, or associated with a particular area, organization, or group.
-
E.
hasHeadquartersBuilding
Indicates that an organization possesses a specific building that serves as its headquarters location.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebfdb0608190b1794a871d0d237a |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e960d880819084b3df4e5137a1e2 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0b23ec8190bef9d593162388a4 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.