Triple
T81907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas A&M University |
E1645
|
entity |
| Predicate | researchActivityLevel |
P3397
|
FINISHED |
| Object | very high research activity |
—
|
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: very high research activity | Statement: [Texas A&M University, researchActivityLevel, very high research activity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: researchActivityLevel Context triple: [Texas A&M University, researchActivityLevel, very high research activity]
-
A.
researchStrength
Indicates the degree to which an entity possesses strong capabilities, performance, or impact in conducting research.
-
B.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
C.
researchClassification
chosen
Indicates that an entity is assigned a specific category or type within a research-related classification scheme.
-
D.
academicFocus
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
E.
researchProgram
Indicates that an entity is engaged in, associated with, or part of a structured research initiative or program.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.