Triple
T22029270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Board of Trustees of the Federal Old-Age and Survivors Insurance and Disability Insurance Trust Funds |
E544042
|
entity |
| Predicate | frequencyOfReport |
P55256
|
FINISHED |
| Object | annually |
—
|
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: annually | Statement: [Board of Trustees of the Federal Old-Age and Survivors Insurance and Disability Insurance Trust Funds, frequencyOfReport, annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyOfReport Context triple: [Board of Trustees of the Federal Old-Age and Survivors Insurance and Disability Insurance Trust Funds, frequencyOfReport, annually]
-
A.
inspectionFrequency
Indicates how often an entity is examined, checked, or reviewed within a given time period.
-
B.
measurementFrequency
Indicates how often a measurement is taken or recorded over time.
-
C.
complicationFrequency
Indicates how often complications occur in relation to a given procedure, condition, or intervention.
-
D.
fireFrequency
Indicates how often fire occurs or is expected to occur within a given area or time period.
-
E.
serviceFrequencyType
chosen
Indicates how often a service occurs or is scheduled within a given time period.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127ebf6d48190b84e7a45bbf9049c |
completed | April 28, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:24 p.m.