Triple
T27028175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montgomery GI Bill |
E680845
|
entity |
| Predicate | benefitUsageLimit |
P98726
|
FINISHED |
| Object | typically 36 months of full-time benefits |
—
|
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: typically 36 months of full-time benefits | Statement: [Montgomery GI Bill, benefitUsageLimit, typically 36 months of full-time benefits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitUsageLimit Context triple: [Montgomery GI Bill, benefitUsageLimit, typically 36 months of full-time benefits]
-
A.
volumeLimitationBasis
Indicates the rule, criterion, or reference measure used as the basis for determining a limitation on volume.
-
B.
hasLimitation
Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
-
C.
guaranteeLimitBasis
Indicates the basis or criteria used to determine the limit of a guarantee in a contractual or financial context.
-
D.
maximumUsage
chosen
Indicates the highest allowable or observed amount, frequency, or extent to which something can be used within a defined context or period.
-
E.
dailyQuota
Indicates the maximum amount or limit allocated or allowed for an entity within a single day.
- 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 7:12 a.m.