Triple
T13108077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civil and Environmental Engineering |
E310900
|
entity |
| Predicate | leadsToDegree |
P105261
|
FINISHED |
| Object | Bachelor of 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: Bachelor of Engineering | Statement: [Civil and Environmental Engineering, leadsToDegree, Bachelor of Engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadsToDegree Context triple: [Civil and Environmental Engineering, leadsToDegree, Bachelor of Engineering]
-
A.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
B.
grantsDegreeIn
chosen
Indicates that an institution or authority confers an academic degree in a specified field or discipline.
-
C.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
-
D.
notionOfDegree
Indicates a relationship where one entity specifies or characterizes the degree, intensity, or extent to which a property or condition applies to another entity.
-
E.
grantedDegreesTo
Indicates that one entity has officially conferred academic degrees upon another entity.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817ce07881909ec552bf861ac175 |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98041a3548190a05ddd83dbb660fa |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:05 p.m.