Triple
T37826487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staci Gruber |
E943073
|
entity |
| Predicate | topicOfResearch |
P24329
|
FINISHED |
| Object | effects of early-onset cannabis use |
—
|
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: effects of early-onset cannabis use | Statement: [Staci Gruber, topicOfResearch, effects of early-onset cannabis use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicOfResearch Context triple: [Staci Gruber, topicOfResearch, effects of early-onset cannabis use]
-
A.
researchTopic
chosen
Indicates that a subject conducts or focuses research on a particular topic or area of study.
-
B.
usesResearchSubject
Indicates that one entity employs or utilizes another entity as a research subject in a study or investigation.
-
C.
conductedResearchOn
Indicates that an entity has performed or carried out research concerning another entity or topic.
-
D.
coordinatesResearchOn
Indicates that one entity organizes and directs the planning, execution, and integration of research activities involving another entity.
-
E.
researchValue
Indicates that something is considered useful, important, or relevant for research or scholarly investigation.
- 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_69f76eea4c8c8190a335aed5955cf2db |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.