Triple
T11712493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burke–Wadsworth Act |
E278405
|
entity |
| Predicate | maximumInitialTrainingPeriod |
P74511
|
FINISHED |
| Object | 12 months |
—
|
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: 12 months | Statement: [Burke–Wadsworth Act, maximumInitialTrainingPeriod, 12 months]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumInitialTrainingPeriod Context triple: [Burke–Wadsworth Act, maximumInitialTrainingPeriod, 12 months]
-
A.
maximumInitialValidity
chosen
Indicates the greatest allowable length of time that an initial validity period for something (such as a status, permission, or agreement) may last.
-
B.
durationInitial
Indicates the initial length of time associated with an event, state, or process at its starting point.
-
C.
earlyTraining
Indicates that an entity receives or provides training at an early stage relative to a process, development period, or typical timeline.
-
D.
maximumAccrualPeriod
Indicates the longest time span over which something (such as interest, benefits, or rights) can accumulate before it stops accruing.
-
E.
includesTrainingPhase
Indicates that something contains or encompasses a specific training phase as part of its overall process or structure.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4be10088190854699385d1f6a95 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.