Triple
T1190102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Maryland |
E25337
|
entity |
| Predicate | academicDisciplineStrength |
P366
|
FINISHED |
| Object | engineering |
—
|
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: engineering | Statement: [University of Maryland, academicDisciplineStrength, engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicDisciplineStrength Context triple: [University of Maryland, academicDisciplineStrength, engineering]
-
A.
researchStrength
chosen
Indicates the degree to which an entity possesses strong capabilities, performance, or impact in conducting research.
-
B.
academicReputation
Indicates the perceived quality and standing of an entity within the academic community, based on factors like scholarly impact, prestige, and recognition.
-
C.
academicFocus
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
D.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
E.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
- 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd58d8d88190b8d9c9c9de7f4e97 |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.