Triple
T27566086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Maritime Law |
E695903
|
entity |
| Predicate | regulatesStudyField |
P179787
|
FINISHED |
| Object | courses on shipping and navigation law |
—
|
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: courses on shipping and navigation law | Statement: [Department of Maritime Law, regulatesStudyField, courses on shipping and navigation law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatesStudyField Context triple: [Department of Maritime Law, regulatesStudyField, courses on shipping and navigation law]
-
A.
isPartOfStudyField
Indicates that one subject, topic, or subfield belongs to, is included within, or is a component of a broader academic or research field.
-
B.
characterFieldOfStudy
Indicates the academic or disciplinary field that a character studies or specializes in.
-
C.
jurisdictionOfStudy
Indicates the legal or geographic jurisdiction within which a given study is conducted or governed.
-
D.
regionOfStudy
Indicates the academic or research area that is the focus of someone’s study or investigation.
-
E.
dimensionOfStudy
Indicates the specific field, aspect, or perspective that characterizes or structures a particular study or research activity.
- F. None of above. chosen
Provenance (4 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_69ef53891af88190a193c5e2a1dac9b1 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
| PDg | Predicate description generation | batch_69f727ad9ff88190ba8069dd48b2e98f |
completed | May 3, 2026, 10:47 a.m. |
Created at: April 27, 2026, 1:41 p.m.