Triple
T440097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Model Code of Judicial Conduct |
E10095
|
entity |
| Predicate | creatorType |
P13180
|
FINISHED |
| Object | professional association |
—
|
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: professional association | Statement: [Model Code of Judicial Conduct, creatorType, professional association]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creatorType Context triple: [Model Code of Judicial Conduct, creatorType, professional association]
-
A.
coCreator
Indicates that two or more entities jointly created or produced something together.
-
B.
createdBy
Indicates that something was brought into existence, produced, or authored through the actions or efforts of a specific agent or entity.
-
C.
creatorNationality
Indicates that the creator of an entity has a specified national affiliation or citizenship.
-
D.
creatorBirthName
Indicates the full birth name originally given to the creator of a work or entity.
-
E.
coCreatedWith
Indicates that an entity participated jointly with another entity in the creation or production of something.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef2977888190a0590b2c1bd2f5da |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddcf50c8190bfa0d1f8ee9f604a |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb9e6b0819093863959a6e5730a |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.