Triple
T783364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Court of Appeals for the District of Columbia Circuit |
E16546
|
entity |
| Predicate | subjectMatterSpecialty |
P466
|
FINISHED |
| Object | administrative 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: administrative law | Statement: [United States Court of Appeals for the District of Columbia Circuit, subjectMatterSpecialty, administrative law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectMatterSpecialty Context triple: [United States Court of Appeals for the District of Columbia Circuit, subjectMatterSpecialty, administrative law]
-
A.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
B.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
C.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
D.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
E.
subjectOfWork
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7686d0881908c2a4395059be02c |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.