Triple
T28853697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R. Rex Parris Law Firm |
E728674
|
entity |
| Predicate | caseTypeFocus |
P31647
|
FINISHED |
| Object | high-profile litigation |
—
|
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: high-profile litigation | Statement: [R. Rex Parris Law Firm, caseTypeFocus, high-profile litigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseTypeFocus Context triple: [R. Rex Parris Law Firm, caseTypeFocus, high-profile litigation]
-
A.
focusType
chosen
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
B.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
C.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
-
D.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
E.
focusShift
Indicates a change in attention or emphasis from one entity or topic to another.
- 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_69f0319f4e5481909e4c439dbe8be940 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f659db52f48190a610183087d3b39d |
completed | May 2, 2026, 8:08 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 6:44 a.m.