Triple
T17102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .gov |
E339
|
entity |
| Predicate | governingPolicy |
P1051
|
FINISHED |
| Object | U.S. government domain policies |
—
|
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: U.S. government domain policies | Statement: [.gov, governingPolicy, U.S. government domain policies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governingPolicy Context triple: [.gov, governingPolicy, U.S. government domain policies]
-
A.
admissionPolicy
Indicates the rules or criteria governing whether and how entities are allowed to be admitted or granted access.
-
B.
implementedPolicy
Indicates that a particular policy has been put into effect or carried out by an entity.
-
C.
governance
Indicates the relationship in which one entity exercises authority, control, or decision-making power over the policies, actions, or direction of another entity or system.
-
D.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
E.
legalBasis
Indicates the legal rule, authority, or justification under which an action, decision, or status is established or carried out.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a241ea1ea081908e8a81ca97531ba5 |
completed | Feb. 28, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69a23fec1fe8819080da6f2c745dc8fd |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a241e933288190b02ef5369f7b8834 |
completed | Feb. 28, 2026, 1:16 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.