Triple
T31216302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empirical analysis of the Mariel boatlift and its impact on Miami labor markets |
E795879
|
entity |
| Predicate | researchDesign |
P98380
|
FINISHED |
| Object | quasi-experimental |
—
|
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: quasi-experimental | Statement: [Empirical analysis of the Mariel boatlift and its impact on Miami labor markets, researchDesign, quasi-experimental]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: researchDesign Context triple: [Empirical analysis of the Mariel boatlift and its impact on Miami labor markets, researchDesign, quasi-experimental]
-
A.
studyDesign
chosen
Indicates the type or structure of the research methodology or experimental setup used in a study.
-
B.
researchMode
Indicates that an entity is engaged in or configured for conducting systematic investigation, experimentation, or study.
-
C.
researchComponent
Indicates that an entity functions as a part or element within a broader research activity, project, or study.
-
D.
researchValue
Indicates that something is considered useful, important, or relevant for research or scholarly investigation.
-
E.
researchModel
Indicates that an entity systematically investigates, develops, or analyzes a model as part of a research process.
- 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_69f224d9d52c8190a61f68ded37fa755 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69dfdda708190be290c7bec205445 |
completed | May 3, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69f69d1a37e081908d1d86b90ff502bd |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:10 p.m.