Triple
T18316127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese American Redress Act |
E438757
|
entity |
| Predicate | typeOfCompensation |
P14176
|
FINISHED |
| Object | individual payments |
—
|
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: individual payments | Statement: [Japanese American Redress Act, typeOfCompensation, individual payments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCompensation Context triple: [Japanese American Redress Act, typeOfCompensation, individual payments]
-
A.
compensationCategory
chosen
Indicates the type or classification of compensation associated with an entity, such as how or in what form payment or remuneration is provided.
-
B.
compensationModel
Indicates the type or structure of payment or rewards provided in exchange for work, services, or performance.
-
C.
salaryType
Indicates the classification or structure of compensation associated with an entity, such as whether pay is salaried, hourly, commission-based, or another type.
-
D.
providedCompensationAmount
Indicates the specific amount of compensation that was given or agreed to be given in relation to an action, event, or obligation.
-
E.
salary
Indicates the amount of monetary compensation an entity receives, typically on a regular basis, for work or services performed.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021e61008190a300b6c51976a837 |
completed | April 19, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.