Triple
T17061777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Delaware |
E413976
|
entity |
| Predicate | hasNotableAreaOfPractice |
P17432
|
FINISHED |
| Object | intellectual property 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: intellectual property law | Statement: [District of Delaware, hasNotableAreaOfPractice, intellectual property law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableAreaOfPractice Context triple: [District of Delaware, hasNotableAreaOfPractice, intellectual property law]
-
A.
regionOfPractice
Indicates the geographic area or jurisdiction in which an entity regularly conducts its professional activities or services.
-
B.
hasLanguageOfPractice
Indicates that an entity uses or operates in a particular language as its regular or primary medium of practice.
-
C.
hasNotablePracticeStatus
Indicates that an entity holds a recognized or distinguished status regarding its professional, operational, or practice-related activities.
-
D.
hasPracticeFields
chosen
Indicates that an entity possesses or is associated with one or more designated fields or areas used for practice activities.
-
E.
practicedInField
Indicates that an entity has engaged in practical work, training, or professional activity within a specified field or domain.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db7dea7481909e3e0bc836d27336 |
completed | April 18, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.