Triple
T2238369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medal of Valor |
E49335
|
entity |
| Predicate | benefitsToRecipient |
P487
|
FINISHED |
| Object | special pension |
—
|
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: special pension | Statement: [Medal of Valor, benefitsToRecipient, special pension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitsToRecipient Context triple: [Medal of Valor, benefitsToRecipient, special pension]
-
A.
beneficiaries
Indicates that certain entities receive advantages, profits, or positive outcomes from an action, event, or arrangement.
-
B.
benefitsState
Indicates that one entity provides an advantage, improvement, or positive outcome to a state or governmental entity.
-
C.
benefits
chosen
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
D.
beneficiaryType
Indicates the type or category of beneficiary that receives or is intended to receive the benefit or outcome of an action or resource.
-
E.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc096c7748190a545cc9b229bde62 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.