Triple
T1022336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Veterans Affairs Act |
E22065
|
entity |
| Predicate | hasBeneficiaryClass |
P22506
|
FINISHED |
| Object | United States veterans |
—
|
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: United States veterans | Statement: [Department of Veterans Affairs Act, hasBeneficiaryClass, United States veterans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeneficiaryClass Context triple: [Department of Veterans Affairs Act, hasBeneficiaryClass, United States veterans]
-
A.
beneficiaryType
chosen
Indicates the type or category of beneficiary that receives or is intended to receive the benefit or outcome of an action or resource.
-
B.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
C.
hasTypeOfRecipient
Indicates that an entity is associated with a specific category or kind of recipient it is intended for or directed to.
-
D.
beneficiaries
Indicates that certain entities receive advantages, profits, or positive outcomes from an action, event, or arrangement.
-
E.
hasAdherent
Indicates that an entity is a follower, supporter, or member attached to another entity (such as a person, organization, belief, or movement).
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7dead9c8190a0f8d4ef48e6c809 |
completed | March 1, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69a4b724c7908190a5b92a57fbdbff4e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.