Triple
T36674786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graduate Program in Communication |
E905513
|
entity |
| Predicate | researchAreasMayInclude |
P934
|
FINISHED |
| Object | interpersonal communication |
—
|
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: interpersonal communication | Statement: [Graduate Program in Communication, researchAreasMayInclude, interpersonal communication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: researchAreasMayInclude Context triple: [Graduate Program in Communication, researchAreasMayInclude, interpersonal communication]
-
A.
hasResearchArea
chosen
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
B.
researchTopic
Indicates that a subject conducts or focuses research on a particular topic or area of study.
-
C.
regionOfStudy
Indicates the academic or research area that is the focus of someone’s study or investigation.
-
D.
isInResearchArea
Indicates that one entity falls within, or is relevant to, the specified research area of another entity.
-
E.
regionOfAcademicInterest
Indicates that an entity has a particular academic field or subject area as its focus of interest or study.
- 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_69f76e6f10008190aea41746aa1b186e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c7a1e71081909b8eebef98c15437 |
completed | May 3, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.