Triple
T10263026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | public TSCA Inventory |
E240645
|
entity |
| Predicate | primaryUserGroups |
P93003
|
FINISHED |
| Object | industry compliance professionals |
—
|
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: industry compliance professionals | Statement: [public TSCA Inventory, primaryUserGroups, industry compliance professionals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryUserGroups Context triple: [public TSCA Inventory, primaryUserGroups, industry compliance professionals]
-
A.
primaryUserGroup
Indicates the main or default user group to which a user is primarily assigned or associated.
-
B.
primaryUsersRole
Indicates the role that a primary user holds in relation to a given resource, system, or context.
-
C.
primaryUser
Indicates that the referenced user is the main or principal user associated with a given account, resource, or context.
-
D.
primaryUserType
Indicates the main or dominant category of user associated with an entity or interaction.
-
E.
secondaryUserGroup
Indicates a relationship where a user is associated with an additional, non-primary group that supplements their main group membership.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2872830819080fdfa816167d04c |
completed | April 7, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ef6e6c81908a8ee52e4d28127b |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d285812c8190ab910dc85c53eebf |
completed | April 7, 2026, 9:46 a.m. |
Created at: April 6, 2026, 11:33 a.m.