Triple
T25620904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GINA |
E642292
|
entity |
| Predicate | Title II regulates |
P171732
|
FINISHED |
| Object | employers |
—
|
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: employers | Statement: [GINA, Title II regulates, employers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Title II regulates Context triple: [GINA, Title II regulates, employers]
-
A.
Title I regulates
Indicates that Title I is the legal authority that imposes rules, requirements, or restrictions on a specified subject or activity.
-
B.
annexIIRegulates
Indicates that Annex II establishes rules, controls, or requirements governing the target entity or activity.
-
C.
regulatesTitle
Indicates that one entity has the authority or function to control, govern, or set rules regarding another entity’s official title.
-
D.
alsoRegulates
Indicates that an entity not only has a primary regulatory effect on a target but additionally regulates that same target through another, supplementary regulatory relationship.
-
E.
regulationAtIssue
Indicates that a specific regulation is the subject of concern, dispute, or analysis in the given context.
- 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_69e77e7a96748190b10f2699041e4e43 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a28b8ea881908733485374771c51 |
completed | May 3, 2026, 1:19 a.m. |
Created at: April 21, 2026, 5:04 p.m.