Triple
T2565003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selective Training and Service Act of 1940 |
E57330
|
entity |
| Predicate | laterServiceObligationLength |
P24237
|
FINISHED |
| Object | 18 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: 18 months | Statement: [Selective Training and Service Act of 1940, laterServiceObligationLength, 18 months]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterServiceObligationLength Context triple: [Selective Training and Service Act of 1940, laterServiceObligationLength, 18 months]
-
A.
possibleLengthDays
Indicates that an entity can have a duration, measured in whole or fractional days, equal to the specified value.
-
B.
possibleDuration
chosen
Indicates the range or specific length of time that an action, event, or state can last or is allowed to last.
-
C.
plannedExtensionLength
Indicates the intended or proposed length of an extension as specified in a plan or design.
-
D.
commitmentTiming
Indicates the point in time or period relative to an event or agreement when a commitment is made, becomes effective, or is expected to be fulfilled.
-
E.
occupationDuration
Indicates the length of time an entity holds or has held a particular occupation or role.
- 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35dce0081909fcac5ac5ad6b841 |
completed | March 7, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69abd0cc8d308190ae7aa32b8f5ae2e5 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.