Triple
T11974622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army Clause |
E285006
|
entity |
| Predicate | maximumAppropriationTerm |
P102589
|
FINISHED |
| Object | two years |
—
|
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: two years | Statement: [Army Clause, maximumAppropriationTerm, two years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumAppropriationTerm Context triple: [Army Clause, maximumAppropriationTerm, two years]
-
A.
maximumAccrualPeriod
Indicates the longest time span over which something (such as interest, benefits, or rights) can accumulate before it stops accruing.
-
B.
maximumTermCount
Indicates the highest number of terms that are allowed or considered within a given context or operation.
-
C.
maximumConsecutiveTerms
Indicates the greatest number of terms that can occur in an unbroken, continuous sequence within a given context or structure.
-
D.
maximumUsage
Indicates the highest allowable or observed amount, frequency, or extent to which something can be used within a defined context or period.
-
E.
maximumBondMaturity
Indicates the longest allowable or actual time period until a bond tied to an entity reaches its maturity date.
- F. None of above. chosen
Provenance (4 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9039107e48190ae4c4efd6257dd3c |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:46 p.m.