Triple
T14005353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BPS-9 |
E336931
|
entity |
| Predicate | retirementBenefitsInclude |
P107203
|
FINISHED |
| Object | pension |
—
|
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: pension | Statement: [BPS-9, retirementBenefitsInclude, pension]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: retirementBenefitsInclude Context triple: [BPS-9, retirementBenefitsInclude, pension]
-
A.
appliesToRetirementStatus
Indicates that the subject is relevant or applicable specifically to an entity’s retirement status or condition.
-
B.
receivesPensionFrom
Indicates that one entity is the source or provider of a pension that another entity receives.
-
C.
compensationIncludes
chosen
Indicates that a specified form of payment or benefit is part of the overall compensation provided in a given context.
-
D.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
E.
benefitProgramInvolved
Indicates that a benefit program participates in, is associated with, or plays a role in the referenced situation or relationship.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed1d2548190bb46d6b7cba4ffde |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:19 p.m.