Triple
T7420427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Health Sciences |
E171231
|
entity |
| Predicate | mayHaveUnit |
P76861
|
FINISHED |
| Object | department of medicine |
—
|
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: department of medicine | Statement: [College of Health Sciences, mayHaveUnit, department of medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayHaveUnit Context triple: [College of Health Sciences, mayHaveUnit, department of medicine]
-
A.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
B.
multipleUnit
Indicates that an entity is composed of or associated with more than one unit of the same type.
-
C.
mayHaveStructure
Indicates that an entity is allowed or able to possess a particular internal organization, configuration, or structural form, though not necessarily required to do so.
-
D.
supportedUnit
Indicates that one entity provides assistance, resources, or backing to another entity functioning as a unit or sub-organization.
-
E.
unitOfMeasure
Indicates that one entity specifies the standard unit in which the quantity or value of another entity is measured.
- F. None of above. chosen
Provenance (4 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2ea61248190886e8e55b42ba5f1 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1c3307481909a7f6bb69d4fddac |
completed | March 27, 2026, 9:08 p.m. |
Created at: March 27, 2026, 3:11 p.m.