Triple
T17849776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John C. Flanagan |
E445765
|
entity |
| Predicate | appliedResearchIn |
P83724
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [John C. Flanagan, appliedResearchIn, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedResearchIn Context triple: [John C. Flanagan, appliedResearchIn, education]
-
A.
appliesResearchTo
chosen
Indicates that an entity uses or implements research findings, methods, or insights in relation to another entity, context, or problem.
-
B.
researchValue
Indicates that something is considered useful, important, or relevant for research or scholarly investigation.
-
C.
supportedResearch
Indicates that one entity provided assistance, resources, or backing to enable or advance the research activities of another entity.
-
D.
motivatedResearchIn
Indicates that one entity inspired, drove, or provided the motivation for another entity to conduct a particular research activity or line of inquiry.
-
E.
usedResearchFrom
Indicates that one entity based its work, findings, or outputs on research conducted or provided by another entity.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffe415c8190aed351c52b78a143 |
completed | April 19, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e266888190ae976b4b7d5b886f |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:16 a.m.