Triple
T3667476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Science Center (Harvard University) |
E77795
|
entity |
| Predicate | servesAcademicDiscipline |
P43754
|
FINISHED |
| Object | physics |
—
|
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: physics | Statement: [Science Center (Harvard University), servesAcademicDiscipline, physics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesAcademicDiscipline Context triple: [Science Center (Harvard University), servesAcademicDiscipline, physics]
-
A.
servesAcademicUnit
Indicates that one entity performs services or functions in support of, or on behalf of, an academic unit.
-
B.
regionOfAcademicFocus
chosen
Indicates the academic subject area or discipline that an entity (such as a person or program) primarily concentrates on or specializes in.
-
C.
hasAcademicComponent
Indicates that something includes, involves, or is associated with an academic or educational element as part of its structure or content.
-
D.
hasInfluenceOnDiscipline
Indicates that one entity exerts an effect, shaping force, or contributing impact on the development, direction, or state of a particular discipline.
-
E.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
- 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc402f5dc8190bd8d56a3c06e88f3 |
completed | March 8, 2026, 6:46 p.m. |
| PD | Predicate disambiguation | batch_69adb84a20288190a092e4a1b045fe3f |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.