Triple
T2362561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tecnológico de Monterrey |
E47306
|
entity |
| Predicate | hasResearchCenters |
P38229
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tecnológico de Monterrey, hasResearchCenters, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResearchCenters Context triple: [Tecnológico de Monterrey, hasResearchCenters, yes]
-
A.
hasResearchCentersIn
Indicates that an entity maintains or operates research centers located within a specified place or region.
-
B.
numberOfResearchCentres
Indicates the quantity of research centres associated with a given entity.
-
C.
researchCenter
Indicates that one entity functions as a research center associated with, operated by, or focused on the other entity.
-
D.
hasResearchHospital
Indicates that an entity possesses, is associated with, or operates a hospital facility dedicated to conducting medical or clinical research.
-
E.
containsResearchStation
Indicates that one entity geographically includes or hosts a research station within its boundaries.
- 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_69a88a1a4a6081908645b0f2914521ab |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc74501388190adce9b3e51a03ded |
completed | March 7, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69abc599b92c819093d9e15d4437705d |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6a85e2c8190afec217ff29476be |
completed | March 7, 2026, 6:33 a.m. |
Created at: March 4, 2026, 7:55 p.m.