Triple
T238045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tribology Division |
E4865
|
entity |
| Predicate | hasParentDiscipline |
P5484
|
FINISHED |
| Object | mechanical 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: mechanical engineering | Statement: [Tribology Division, hasParentDiscipline, mechanical engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParentDiscipline Context triple: [Tribology Division, hasParentDiscipline, mechanical engineering]
-
A.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
B.
subDisciplineOf
chosen
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
C.
associatedWithDiscipline
Indicates that an entity has a relevant connection or involvement with a particular academic, professional, or thematic discipline.
-
D.
supportsDiscipline
Indicates that one entity provides assistance, resources, or endorsement that helps sustain or advance a particular discipline.
-
E.
studiedUnder
Indicates that one entity received instruction, training, or mentorship from another, typically in an academic or apprenticeship context.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dacf60c8190a5c3ef455b9a8b20 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b5f27208190ae13f34037fe582b |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.