Triple
T2362567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tecnológico de Monterrey |
E47306
|
entity |
| Predicate | regionallyRankedAmong |
P13048
|
FINISHED |
| Object | top universities in Latin America |
—
|
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: top universities in Latin America | Statement: [Tecnológico de Monterrey, regionallyRankedAmong, top universities in Latin America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionallyRankedAmong Context triple: [Tecnológico de Monterrey, regionallyRankedAmong, top universities in Latin America]
-
A.
rankedAmong
Indicates that an entity holds a specific position or status within a defined group, list, or hierarchy of comparable entities.
-
B.
regionRankContext
chosen
Indicates the relative ranking or position of something within a specific geographic or regional context.
-
C.
rankedAs
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
-
D.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
E.
nationalRank
Indicates the position or standing of an entity within a ranking system at the national level.
- 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_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. |
Created at: March 4, 2026, 7:55 p.m.