Triple
T13067387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J. R. Clifford |
E329362
|
entity |
| Predicate | legalFocus |
P68507
|
FINISHED |
| Object | civil rights 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: civil rights law | Statement: [J. R. Clifford, legalFocus, civil rights law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalFocus Context triple: [J. R. Clifford, legalFocus, civil rights law]
-
A.
legalCodeFocus
chosen
Indicates that something is specifically concerned with, centered on, or primarily addressing a particular legal code or body of law.
-
B.
legalTool
Indicates a relationship where something functions as a legal instrument, mechanism, or means used to achieve or regulate a legal purpose or outcome.
-
C.
legalMatters
Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
-
D.
legalForum
Indicates the official legal venue or jurisdiction in which a dispute, case, or legal matter is to be heard or resolved.
-
E.
legalBackground
Indicates that an entity has education, training, or experience related to law or the legal profession.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ec8ba48190baf52c7823482680 |
completed | April 10, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9 p.m.