Triple
T30550566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Mechanical Engineering |
E777545
|
entity |
| Predicate | offersSpecializationIn |
P2902
|
FINISHED |
| Object | machine design |
—
|
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: machine design | Statement: [Department of Mechanical Engineering, offersSpecializationIn, machine design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersSpecializationIn Context triple: [Department of Mechanical Engineering, offersSpecializationIn, machine design]
-
A.
offersEducationIn
Indicates that an entity provides or delivers educational programs, courses, or instruction in a specified field, subject, or area.
-
B.
offersSpecialtyCare
Indicates that an entity provides specialized or advanced care services beyond general or primary care.
-
C.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
D.
offersDiscipline
chosen
Indicates that one entity provides or makes available a particular field of study, training, or area of specialization to another entity.
-
E.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
- 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_69f2249e19108190a458ab446096bf22 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: April 29, 2026, 8:20 p.m.